02_2020-023_asv_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.stats import kruskal\n",
    "import seaborn as sns\n",
    "from matplotlib.patches import Ellipse\n",
    "import matplotlib.transforms as transforms\n",
    "import matplotlib.pyplot as plt  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import qiime2\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiime2 import Visualization\n",
    "from qiime2 import Artifact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skbio import OrdinationResults"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load ASV\n",
    "PSC_ASV_seren= pd.read_csv('./results/PSC_ASV_seren.csv', index_col=0)\n",
    "PSC_ASV_stool= pd.read_csv('./results/PSC_ASV_stool.csv', index_col=0)\n",
    "\n",
    "BSPSPC_ASV_seren= pd.read_csv('./results/BSPSPC_ASV_seren.csv', index_col=0)\n",
    "BSPSPC_ASV_stool= pd.read_csv('./results/BSPSPC_ASV_stool.csv', index_col=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load taxonomy\n",
    "#PSC Seren\n",
    "PSC_tax_seren = pd.read_csv('./P2N_2020-023_Corinna_Bang/2020-023_16s_Seren_2020_06_asv_seqs_and_annotation_Bayesian_RDP16.tsv', sep='\\t', index_col=0)\n",
    "\n",
    "#PSC Stool\n",
    "PSC_tax_stool = pd.read_csv('./P2N_2020-023_Corinna_Bang/2020-023_16s_Stool_2020_06_asv_seqs_and_annotation_Bayesian_RDP16.tsv', sep='\\t', index_col=0)\n",
    "\n",
    "\n",
    "#BSPSPC Seren\n",
    "BSPSPC_tax_seren = pd.read_csv('./P2N_2020-023_Corinna_Bang/2020-023_16s_Seren_asv_seqs_and_annotation_Bayesian_RDP16.tsv', sep='\\t', index_col=0)\n",
    "\n",
    "\n",
    "#BSPSPC Stool\n",
    "BSPSPC_tax_stool = pd.read_csv('./P2N_2020-023_Corinna_Bang/2020-023_16s_Stool_BSPSPC_asv_seqs_and_annotation_Bayesian_RDP16.tsv', sep='\\t', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_seren.index = PSC_ASV_seren.index + \"_srn\"\n",
    "PSC_ASV_stool.index = PSC_ASV_stool.index + \"_stl\"\n",
    "\n",
    "BSPSPC_ASV_seren.index = BSPSPC_ASV_seren.index + \"_srn\"\n",
    "BSPSPC_ASV_stool.index = BSPSPC_ASV_stool.index + \"_stl\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Find common seqs for stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "common_rows = PSC_tax_stool['seq'].isin(BSPSPC_tax_stool['seq'])\n",
    "common_rows = common_rows[common_rows].index\n",
    "PSC_tax_stool_common = PSC_tax_stool[PSC_tax_stool.index.isin(common_rows)]\n",
    "PSC_tax_stool_common = PSC_tax_stool_common.sort_values(by='seq')\n",
    "PSC_tax_stool_common['mASV'] = ['ASV_' + str(i) for i in range(1, len(PSC_tax_stool_common) + 1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seq</th>\n",
       "      <th>Kingdom</th>\n",
       "      <th>Phylum</th>\n",
       "      <th>Class</th>\n",
       "      <th>Order</th>\n",
       "      <th>Family</th>\n",
       "      <th>Genus</th>\n",
       "      <th>Species</th>\n",
       "      <th>mASV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seqname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_17745</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAACGGGAGCAGCAA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Tenericutes</td>\n",
       "      <td>C__Mollicutes</td>\n",
       "      <td>O__Anaeroplasmatales</td>\n",
       "      <td>F__Anaeroplasmataceae</td>\n",
       "      <td>G__Asteroleplasma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_484</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAGCGGGGCCCGCAA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Tenericutes</td>\n",
       "      <td>C__Mollicutes</td>\n",
       "      <td>O__Anaeroplasmatales</td>\n",
       "      <td>F__Anaeroplasmataceae</td>\n",
       "      <td>G__Asteroleplasma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_4552</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGGACGGGGCGGGGGA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Tenericutes</td>\n",
       "      <td>C__Mollicutes</td>\n",
       "      <td>O__Anaeroplasmatales</td>\n",
       "      <td>F__Anaeroplasmataceae</td>\n",
       "      <td>G__Asteroleplasma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_8881</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCACTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_3516</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_13528</th>\n",
       "      <td>ATGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGAAGCACTTTG...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>G__Roseburia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_21277</th>\n",
       "      <td>GCGGATCGTGCTGGTCGTCACCCACGACCGGGAGTTTATGCAACGC...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_10204</th>\n",
       "      <td>GGAATAACGTAGGGAAACCTGCACTAATACCGCATAATGTACAGGG...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Ruminococcaceae</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_23144</th>\n",
       "      <td>GGGATAACAGTTAGAAATAGCTGCTAATACCGCATAAGCGCACGGT...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_21313</th>\n",
       "      <td>GGGATAACAGTTAGAAATGACTGCTAATACCGCATAAGCGCACGGT...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>G__Clostridium_XlVa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13719</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13719 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         seq      Kingdom  \\\n",
       "seqname                                                                     \n",
       "ASV_17745  ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAACGGGAGCAGCAA...  K__Bacteria   \n",
       "ASV_484    ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAGCGGGGCCCGCAA...  K__Bacteria   \n",
       "ASV_4552   ACGCCGGCGGCGTGCCTAATACATGCAAGTCGGACGGGGCGGGGGA...  K__Bacteria   \n",
       "ASV_8881   ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCACTGGCCCA...  K__Bacteria   \n",
       "ASV_3516   ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "...                                                      ...          ...   \n",
       "ASV_13528  ATGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGAAGCACTTTG...  K__Bacteria   \n",
       "ASV_21277  GCGGATCGTGCTGGTCGTCACCCACGACCGGGAGTTTATGCAACGC...          NaN   \n",
       "ASV_10204  GGAATAACGTAGGGAAACCTGCACTAATACCGCATAATGTACAGGG...  K__Bacteria   \n",
       "ASV_23144  GGGATAACAGTTAGAAATAGCTGCTAATACCGCATAAGCGCACGGT...  K__Bacteria   \n",
       "ASV_21313  GGGATAACAGTTAGAAATGACTGCTAATACCGCATAAGCGCACGGT...  K__Bacteria   \n",
       "\n",
       "                   Phylum          Class                 Order  \\\n",
       "seqname                                                          \n",
       "ASV_17745  P__Tenericutes  C__Mollicutes  O__Anaeroplasmatales   \n",
       "ASV_484    P__Tenericutes  C__Mollicutes  O__Anaeroplasmatales   \n",
       "ASV_4552   P__Tenericutes  C__Mollicutes  O__Anaeroplasmatales   \n",
       "ASV_8881    P__Firmicutes     C__Bacilli    O__Lactobacillales   \n",
       "ASV_3516    P__Firmicutes     C__Bacilli    O__Lactobacillales   \n",
       "...                   ...            ...                   ...   \n",
       "ASV_13528   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_21277             NaN            NaN                   NaN   \n",
       "ASV_10204   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_23144   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_21313   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "\n",
       "                          Family                Genus Species       mASV  \n",
       "seqname                                                                   \n",
       "ASV_17745  F__Anaeroplasmataceae    G__Asteroleplasma     NaN      ASV_1  \n",
       "ASV_484    F__Anaeroplasmataceae    G__Asteroleplasma     NaN      ASV_2  \n",
       "ASV_4552   F__Anaeroplasmataceae    G__Asteroleplasma     NaN      ASV_3  \n",
       "ASV_8881     F__Lactobacillaceae     G__Lactobacillus     NaN      ASV_4  \n",
       "ASV_3516     F__Lactobacillaceae     G__Lactobacillus     NaN      ASV_5  \n",
       "...                          ...                  ...     ...        ...  \n",
       "ASV_13528     F__Lachnospiraceae         G__Roseburia     NaN  ASV_13715  \n",
       "ASV_21277                    NaN                  NaN     NaN  ASV_13716  \n",
       "ASV_10204     F__Ruminococcaceae                  NaN     NaN  ASV_13717  \n",
       "ASV_23144     F__Lachnospiraceae                  NaN     NaN  ASV_13718  \n",
       "ASV_21313     F__Lachnospiraceae  G__Clostridium_XlVa     NaN  ASV_13719  \n",
       "\n",
       "[13719 rows x 9 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PSC_tax_stool_common"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seq</th>\n",
       "      <th>Kingdom</th>\n",
       "      <th>Phylum</th>\n",
       "      <th>Class</th>\n",
       "      <th>Order</th>\n",
       "      <th>Family</th>\n",
       "      <th>Genus</th>\n",
       "      <th>Species</th>\n",
       "      <th>mASV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seqname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_597</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1663</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1672</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                        seq      Kingdom  \\\n",
       "seqname                                                                    \n",
       "ASV_597   ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "ASV_1663  ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "ASV_1672  ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "\n",
       "                 Phylum       Class               Order               Family  \\\n",
       "seqname                                                                        \n",
       "ASV_597   P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "ASV_1663  P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "ASV_1672  P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "\n",
       "                     Genus                   Species    mASV  \n",
       "seqname                                                       \n",
       "ASV_597   G__Lactobacillus  S__Lactobacillus_mucosae   ASV_7  \n",
       "ASV_1663  G__Lactobacillus  S__Lactobacillus_mucosae   ASV_8  \n",
       "ASV_1672  G__Lactobacillus  S__Lactobacillus_mucosae  ASV_14  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PSC_tax_stool_common[PSC_tax_stool_common['Species'] == 'S__Lactobacillus_mucosae']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "BSPSPC_common_rows = BSPSPC_tax_stool['seq'].isin(PSC_tax_stool['seq'])\n",
    "BSPSPC_common_rows = BSPSPC_common_rows[BSPSPC_common_rows].index\n",
    "BSPSPC_tax_stool_common = BSPSPC_tax_stool[BSPSPC_tax_stool.index.isin(BSPSPC_common_rows)]\n",
    "BSPSPC_tax_stool_common = BSPSPC_tax_stool_common.sort_values(by='seq')\n",
    "BSPSPC_tax_stool_common['mASV'] = ['ASV_' + str(i) for i in range(1, len(BSPSPC_tax_stool_common) + 1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seq</th>\n",
       "      <th>Kingdom</th>\n",
       "      <th>Phylum</th>\n",
       "      <th>Class</th>\n",
       "      <th>Order</th>\n",
       "      <th>Family</th>\n",
       "      <th>Genus</th>\n",
       "      <th>Species</th>\n",
       "      <th>mASV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seqname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_2275</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_11216</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_5013</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>S__Lactobacillus_mucosae</td>\n",
       "      <td>ASV_14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         seq      Kingdom  \\\n",
       "seqname                                                                     \n",
       "ASV_2275   ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "ASV_11216  ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "ASV_5013   ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "\n",
       "                  Phylum       Class               Order               Family  \\\n",
       "seqname                                                                         \n",
       "ASV_2275   P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "ASV_11216  P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "ASV_5013   P__Firmicutes  C__Bacilli  O__Lactobacillales  F__Lactobacillaceae   \n",
       "\n",
       "                      Genus                   Species    mASV  \n",
       "seqname                                                        \n",
       "ASV_2275   G__Lactobacillus  S__Lactobacillus_mucosae   ASV_7  \n",
       "ASV_11216  G__Lactobacillus  S__Lactobacillus_mucosae   ASV_8  \n",
       "ASV_5013   G__Lactobacillus  S__Lactobacillus_mucosae  ASV_14  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BSPSPC_tax_stool_common[BSPSPC_tax_stool_common['Species'] == 'S__Lactobacillus_mucosae']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seq</th>\n",
       "      <th>Kingdom</th>\n",
       "      <th>Phylum</th>\n",
       "      <th>Class</th>\n",
       "      <th>Order</th>\n",
       "      <th>Family</th>\n",
       "      <th>Genus</th>\n",
       "      <th>Species</th>\n",
       "      <th>mASV</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seqname</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_26141</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAACGGGAGCAGCAA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Tenericutes</td>\n",
       "      <td>C__Mollicutes</td>\n",
       "      <td>O__Anaeroplasmatales</td>\n",
       "      <td>F__Anaeroplasmataceae</td>\n",
       "      <td>G__Asteroleplasma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_261</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAGCGGGGCCCGCAA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_11180</th>\n",
       "      <td>ACGCCGGCGGCGTGCCTAATACATGCAAGTCGGACGGGGCGGGGGA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Tenericutes</td>\n",
       "      <td>C__Mollicutes</td>\n",
       "      <td>O__Anaeroplasmatales</td>\n",
       "      <td>F__Anaeroplasmataceae</td>\n",
       "      <td>G__Asteroleplasma</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_51529</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCACTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_11047</th>\n",
       "      <td>ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Bacilli</td>\n",
       "      <td>O__Lactobacillales</td>\n",
       "      <td>F__Lactobacillaceae</td>\n",
       "      <td>G__Lactobacillus</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_21597</th>\n",
       "      <td>ATGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGAAGCACTTTG...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>G__Roseburia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_33121</th>\n",
       "      <td>GCGGATCGTGCTGGTCGTCACCCACGACCGGGAGTTTATGCAACGC...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_19002</th>\n",
       "      <td>GGAATAACGTAGGGAAACCTGCACTAATACCGCATAATGTACAGGG...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Ruminococcaceae</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_27561</th>\n",
       "      <td>GGGATAACAGTTAGAAATAGCTGCTAATACCGCATAAGCGCACGGT...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_35112</th>\n",
       "      <td>GGGATAACAGTTAGAAATGACTGCTAATACCGCATAAGCGCACGGT...</td>\n",
       "      <td>K__Bacteria</td>\n",
       "      <td>P__Firmicutes</td>\n",
       "      <td>C__Clostridia</td>\n",
       "      <td>O__Clostridiales</td>\n",
       "      <td>F__Lachnospiraceae</td>\n",
       "      <td>G__Clostridium_XlVa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ASV_13719</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13719 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         seq      Kingdom  \\\n",
       "seqname                                                                     \n",
       "ASV_26141  ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAACGGGAGCAGCAA...  K__Bacteria   \n",
       "ASV_261    ACGCCGGCGGCGTGCCTAATACATGCAAGTCGAGCGGGGCCCGCAA...  K__Bacteria   \n",
       "ASV_11180  ACGCCGGCGGCGTGCCTAATACATGCAAGTCGGACGGGGCGGGGGA...  K__Bacteria   \n",
       "ASV_51529  ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCACTGGCCCA...  K__Bacteria   \n",
       "ASV_11047  ACGCCGGCGGTGTGCCTAATACATGCAAGTCGAACGCGTTGGCCCA...  K__Bacteria   \n",
       "...                                                      ...          ...   \n",
       "ASV_21597  ATGCTGGCGGCGTGCTTAACACATGCAAGTCGAACGAAGCACTTTG...  K__Bacteria   \n",
       "ASV_33121  GCGGATCGTGCTGGTCGTCACCCACGACCGGGAGTTTATGCAACGC...          NaN   \n",
       "ASV_19002  GGAATAACGTAGGGAAACCTGCACTAATACCGCATAATGTACAGGG...  K__Bacteria   \n",
       "ASV_27561  GGGATAACAGTTAGAAATAGCTGCTAATACCGCATAAGCGCACGGT...  K__Bacteria   \n",
       "ASV_35112  GGGATAACAGTTAGAAATGACTGCTAATACCGCATAAGCGCACGGT...  K__Bacteria   \n",
       "\n",
       "                   Phylum          Class                 Order  \\\n",
       "seqname                                                          \n",
       "ASV_26141  P__Tenericutes  C__Mollicutes  O__Anaeroplasmatales   \n",
       "ASV_261               NaN            NaN                   NaN   \n",
       "ASV_11180  P__Tenericutes  C__Mollicutes  O__Anaeroplasmatales   \n",
       "ASV_51529   P__Firmicutes     C__Bacilli    O__Lactobacillales   \n",
       "ASV_11047   P__Firmicutes     C__Bacilli    O__Lactobacillales   \n",
       "...                   ...            ...                   ...   \n",
       "ASV_21597   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_33121             NaN            NaN                   NaN   \n",
       "ASV_19002   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_27561   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "ASV_35112   P__Firmicutes  C__Clostridia      O__Clostridiales   \n",
       "\n",
       "                          Family                Genus Species       mASV  \n",
       "seqname                                                                   \n",
       "ASV_26141  F__Anaeroplasmataceae    G__Asteroleplasma     NaN      ASV_1  \n",
       "ASV_261                      NaN                  NaN     NaN      ASV_2  \n",
       "ASV_11180  F__Anaeroplasmataceae    G__Asteroleplasma     NaN      ASV_3  \n",
       "ASV_51529    F__Lactobacillaceae     G__Lactobacillus     NaN      ASV_4  \n",
       "ASV_11047    F__Lactobacillaceae     G__Lactobacillus     NaN      ASV_5  \n",
       "...                          ...                  ...     ...        ...  \n",
       "ASV_21597     F__Lachnospiraceae         G__Roseburia     NaN  ASV_13715  \n",
       "ASV_33121                    NaN                  NaN     NaN  ASV_13716  \n",
       "ASV_19002     F__Ruminococcaceae                  NaN     NaN  ASV_13717  \n",
       "ASV_27561     F__Lachnospiraceae                  NaN     NaN  ASV_13718  \n",
       "ASV_35112     F__Lachnospiraceae  G__Clostridium_XlVa     NaN  ASV_13719  \n",
       "\n",
       "[13719 rows x 9 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BSPSPC_tax_stool_common"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_tax_stool_common.to_csv('./results/PSC_tax_stool_common.csv', index=True)\n",
    "BSPSPC_tax_stool_common.to_csv('./results/BSPSPC_tax_stool_common.csv', index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## rename ASV in count tables for stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_stool = PSC_ASV_stool.drop(columns = ['phase'], axis=1)\n",
    "PSC_ASV_stool = PSC_ASV_stool.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_stool = pd.concat([PSC_ASV_stool, PSC_tax_stool_common['mASV']], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_stool.dropna(subset=['mASV'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_stool.set_index('mASV', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-023_PSC_0001</th>\n",
       "      <th>2020-023_PSC_0002</th>\n",
       "      <th>2020-023_PSC_0003</th>\n",
       "      <th>2020-023_PSC_0005</th>\n",
       "      <th>2020-023_PSC_0006</th>\n",
       "      <th>2020-023_PSC_0007</th>\n",
       "      <th>2020-023_PSC_0010</th>\n",
       "      <th>2020-023_PSC_0012</th>\n",
       "      <th>2020-023_PSC_0013</th>\n",
       "      <th>2020-023_PSC_0015</th>\n",
       "      <th>...</th>\n",
       "      <th>2020-023_PSC_0771</th>\n",
       "      <th>2020-023_PSC_0772</th>\n",
       "      <th>2020-023_PSC_0773</th>\n",
       "      <th>2020-023_PSC_0774</th>\n",
       "      <th>2020-023_PSC_0775</th>\n",
       "      <th>2020-023_PSC_0778</th>\n",
       "      <th>2020-023_PSC_0779</th>\n",
       "      <th>2020-023_PSC_0780</th>\n",
       "      <th>2020-023_PSC_0781</th>\n",
       "      <th>2020-023_PSC_0783</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mASV</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_1391</th>\n",
       "      <td>128</td>\n",
       "      <td>2904</td>\n",
       "      <td>174</td>\n",
       "      <td>1134</td>\n",
       "      <td>12</td>\n",
       "      <td>5819</td>\n",
       "      <td>0</td>\n",
       "      <td>280</td>\n",
       "      <td>0</td>\n",
       "      <td>1393</td>\n",
       "      <td>...</td>\n",
       "      <td>944</td>\n",
       "      <td>574</td>\n",
       "      <td>108</td>\n",
       "      <td>86</td>\n",
       "      <td>1268</td>\n",
       "      <td>56</td>\n",
       "      <td>640</td>\n",
       "      <td>0</td>\n",
       "      <td>585</td>\n",
       "      <td>209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1179</th>\n",
       "      <td>1159</td>\n",
       "      <td>0</td>\n",
       "      <td>897</td>\n",
       "      <td>41</td>\n",
       "      <td>481</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>425</td>\n",
       "      <td>218</td>\n",
       "      <td>...</td>\n",
       "      <td>247</td>\n",
       "      <td>280</td>\n",
       "      <td>487</td>\n",
       "      <td>158</td>\n",
       "      <td>47</td>\n",
       "      <td>830</td>\n",
       "      <td>1848</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1432</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>507</td>\n",
       "      <td>358</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>640</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>217</td>\n",
       "      <td>131</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1823</td>\n",
       "      <td>27</td>\n",
       "      <td>503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_9133</th>\n",
       "      <td>615</td>\n",
       "      <td>457</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>705</td>\n",
       "      <td>0</td>\n",
       "      <td>3121</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_736</th>\n",
       "      <td>174</td>\n",
       "      <td>635</td>\n",
       "      <td>174</td>\n",
       "      <td>935</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1078</td>\n",
       "      <td>393</td>\n",
       "      <td>244</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>152</td>\n",
       "      <td>0</td>\n",
       "      <td>627</td>\n",
       "      <td>0</td>\n",
       "      <td>882</td>\n",
       "      <td>428</td>\n",
       "      <td>610</td>\n",
       "      <td>1489</td>\n",
       "      <td>917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_10602</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_13718</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_2570</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_9807</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_11637</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13719 rows × 527 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           2020-023_PSC_0001  2020-023_PSC_0002  2020-023_PSC_0003  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                 128               2904                174   \n",
       "ASV_1179                1159                  0                897   \n",
       "ASV_1432                   0                  0                507   \n",
       "ASV_9133                 615                457                  0   \n",
       "ASV_736                  174                635                174   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_13718                  0                  0                  0   \n",
       "ASV_2570                   0                  0                  0   \n",
       "ASV_9807                   0                  0                  0   \n",
       "ASV_11637                  0                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0005  2020-023_PSC_0006  2020-023_PSC_0007  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                1134                 12               5819   \n",
       "ASV_1179                  41                481                  0   \n",
       "ASV_1432                 358                 29                  0   \n",
       "ASV_9133                   0                  4                  0   \n",
       "ASV_736                  935                115                  0   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_13718                  0                  0                  0   \n",
       "ASV_2570                   0                  0                  0   \n",
       "ASV_9807                   0                  0                  0   \n",
       "ASV_11637                  0                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0010  2020-023_PSC_0012  2020-023_PSC_0013  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                   0                280                  0   \n",
       "ASV_1179                   0                 11                425   \n",
       "ASV_1432                   0                  0                  0   \n",
       "ASV_9133                   0                  0                  0   \n",
       "ASV_736                    0               1078                393   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_13718                  0                  0                  0   \n",
       "ASV_2570                   0                  0                  0   \n",
       "ASV_9807                   0                  0                  0   \n",
       "ASV_11637                  0                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0015  ...  2020-023_PSC_0771  2020-023_PSC_0772  \\\n",
       "mASV                          ...                                         \n",
       "ASV_1391                1393  ...                944                574   \n",
       "ASV_1179                 218  ...                247                280   \n",
       "ASV_1432                 640  ...                  0                  0   \n",
       "ASV_9133                   0  ...                  0                  0   \n",
       "ASV_736                  244  ...                  0                152   \n",
       "...                      ...  ...                ...                ...   \n",
       "ASV_10602                  0  ...                  0                  0   \n",
       "ASV_13718                  0  ...                  0                  0   \n",
       "ASV_2570                   0  ...                  0                  0   \n",
       "ASV_9807                   0  ...                  0                  0   \n",
       "ASV_11637                  0  ...                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0773  2020-023_PSC_0774  2020-023_PSC_0775  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                 108                 86               1268   \n",
       "ASV_1179                 487                158                 47   \n",
       "ASV_1432                 217                131                  0   \n",
       "ASV_9133                 705                  0               3121   \n",
       "ASV_736                    0                627                  0   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_13718                  0                  0                  0   \n",
       "ASV_2570                   0                  0                  0   \n",
       "ASV_9807                   0                  0                  0   \n",
       "ASV_11637                  0                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0778  2020-023_PSC_0779  2020-023_PSC_0780  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                  56                640                  0   \n",
       "ASV_1179                 830               1848                 70   \n",
       "ASV_1432                   0                  0               1823   \n",
       "ASV_9133                   0                  0                  0   \n",
       "ASV_736                  882                428                610   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_13718                  0                  0                  0   \n",
       "ASV_2570                   0                  0                  0   \n",
       "ASV_9807                   0                  0                  0   \n",
       "ASV_11637                  0                  0                  0   \n",
       "\n",
       "           2020-023_PSC_0781  2020-023_PSC_0783  \n",
       "mASV                                             \n",
       "ASV_1391                 585                209  \n",
       "ASV_1179                   0                810  \n",
       "ASV_1432                  27                503  \n",
       "ASV_9133                   0                  0  \n",
       "ASV_736                 1489                917  \n",
       "...                      ...                ...  \n",
       "ASV_10602                  0                  0  \n",
       "ASV_13718                  0                  0  \n",
       "ASV_2570                   0                  0  \n",
       "ASV_9807                   0                  0  \n",
       "ASV_11637                  0                  0  \n",
       "\n",
       "[13719 rows x 527 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PSC_ASV_stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#return to normal view\n",
    "PSC_ASV_stool = PSC_ASV_stool.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "BSPSPC_ASV_stool = BSPSPC_ASV_stool.drop(columns = ['phase'], axis=1)\n",
    "BSPSPC_ASV_stool = BSPSPC_ASV_stool.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>new_id</th>\n",
       "      <th>2020-023_BSP_0011</th>\n",
       "      <th>2020-023_BSP_0041</th>\n",
       "      <th>2020-023_BSP_0055</th>\n",
       "      <th>2020-023_BSP_0096</th>\n",
       "      <th>2020-023_BSP_0119</th>\n",
       "      <th>2020-023_BSP_0132</th>\n",
       "      <th>2020-023_BSP_0173</th>\n",
       "      <th>2020-023_BSP_0198</th>\n",
       "      <th>2020-023_BSP_0217</th>\n",
       "      <th>2020-023_BSP_0249</th>\n",
       "      <th>...</th>\n",
       "      <th>2020-023_BSP_0756</th>\n",
       "      <th>2020-023_BSP_0762</th>\n",
       "      <th>2020-023_SPC_0034</th>\n",
       "      <th>2020-023_SPC_0171</th>\n",
       "      <th>2020-023_SPC_0189</th>\n",
       "      <th>2020-023_SPC_0409</th>\n",
       "      <th>2020-023_SPC_0480</th>\n",
       "      <th>2020-023_SPC_0515</th>\n",
       "      <th>2020-023_SPC_0726</th>\n",
       "      <th>2020-023_SPC_0741</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_1</th>\n",
       "      <td>469</td>\n",
       "      <td>227</td>\n",
       "      <td>660</td>\n",
       "      <td>303</td>\n",
       "      <td>198</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>721</td>\n",
       "      <td>5370</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>1310</td>\n",
       "      <td>135</td>\n",
       "      <td>750</td>\n",
       "      <td>0</td>\n",
       "      <td>504</td>\n",
       "      <td>1066</td>\n",
       "      <td>1194</td>\n",
       "      <td>0</td>\n",
       "      <td>764</td>\n",
       "      <td>3190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_2</th>\n",
       "      <td>0</td>\n",
       "      <td>384</td>\n",
       "      <td>0</td>\n",
       "      <td>547</td>\n",
       "      <td>66</td>\n",
       "      <td>114</td>\n",
       "      <td>512</td>\n",
       "      <td>1198</td>\n",
       "      <td>0</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>876</td>\n",
       "      <td>287</td>\n",
       "      <td>1511</td>\n",
       "      <td>1921</td>\n",
       "      <td>4</td>\n",
       "      <td>972</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_3</th>\n",
       "      <td>2235</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>365</td>\n",
       "      <td>305</td>\n",
       "      <td>114</td>\n",
       "      <td>1009</td>\n",
       "      <td>1214</td>\n",
       "      <td>0</td>\n",
       "      <td>287</td>\n",
       "      <td>...</td>\n",
       "      <td>1172</td>\n",
       "      <td>159</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_4</th>\n",
       "      <td>1506</td>\n",
       "      <td>0</td>\n",
       "      <td>380</td>\n",
       "      <td>456</td>\n",
       "      <td>274</td>\n",
       "      <td>38</td>\n",
       "      <td>133</td>\n",
       "      <td>823</td>\n",
       "      <td>366</td>\n",
       "      <td>376</td>\n",
       "      <td>...</td>\n",
       "      <td>1517</td>\n",
       "      <td>0</td>\n",
       "      <td>1123</td>\n",
       "      <td>127</td>\n",
       "      <td>716</td>\n",
       "      <td>1911</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>493</td>\n",
       "      <td>1326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9004</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3382</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>89</td>\n",
       "      <td>2915</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_52160</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_52161</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_52162</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_52163</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_52164</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>52164 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "new_id     2020-023_BSP_0011  2020-023_BSP_0041  2020-023_BSP_0055  \\\n",
       "ASV_1                    469                227                660   \n",
       "ASV_2                      0                384                  0   \n",
       "ASV_3                   2235                  0                  0   \n",
       "ASV_4                   1506                  0                380   \n",
       "ASV_5                      0                  0                 53   \n",
       "...                      ...                ...                ...   \n",
       "ASV_52160                  0                  0                  0   \n",
       "ASV_52161                  0                  0                  0   \n",
       "ASV_52162                  0                  0                  0   \n",
       "ASV_52163                  0                  0                  0   \n",
       "ASV_52164                  0                  0                  0   \n",
       "\n",
       "new_id     2020-023_BSP_0096  2020-023_BSP_0119  2020-023_BSP_0132  \\\n",
       "ASV_1                    303                198                114   \n",
       "ASV_2                    547                 66                114   \n",
       "ASV_3                    365                305                114   \n",
       "ASV_4                    456                274                 38   \n",
       "ASV_5                      0                235                  0   \n",
       "...                      ...                ...                ...   \n",
       "ASV_52160                  0                  0                  0   \n",
       "ASV_52161                  0                  0                  0   \n",
       "ASV_52162                  0                  0                  0   \n",
       "ASV_52163                  0                  0                  0   \n",
       "ASV_52164                  0                  0                  0   \n",
       "\n",
       "new_id     2020-023_BSP_0173  2020-023_BSP_0198  2020-023_BSP_0217  \\\n",
       "ASV_1                      0                721               5370   \n",
       "ASV_2                    512               1198                  0   \n",
       "ASV_3                   1009               1214                  0   \n",
       "ASV_4                    133                823                366   \n",
       "ASV_5                      0                  0               9004   \n",
       "...                      ...                ...                ...   \n",
       "ASV_52160                  0                  0                  0   \n",
       "ASV_52161                  0                  0                  0   \n",
       "ASV_52162                  0                  0                  0   \n",
       "ASV_52163                  0                  0                  0   \n",
       "ASV_52164                  0                  0                  0   \n",
       "\n",
       "new_id     2020-023_BSP_0249  ...  2020-023_BSP_0756  2020-023_BSP_0762  \\\n",
       "ASV_1                    119  ...               1310                135   \n",
       "ASV_2                    127  ...                  0                  0   \n",
       "ASV_3                    287  ...               1172                159   \n",
       "ASV_4                    376  ...               1517                  0   \n",
       "ASV_5                      0  ...                  0               3382   \n",
       "...                      ...  ...                ...                ...   \n",
       "ASV_52160                  0  ...                  0                  0   \n",
       "ASV_52161                  0  ...                  0                  0   \n",
       "ASV_52162                  0  ...                  0                  0   \n",
       "ASV_52163                  0  ...                  0                  0   \n",
       "ASV_52164                  0  ...                  0                  0   \n",
       "\n",
       "new_id     2020-023_SPC_0034  2020-023_SPC_0171  2020-023_SPC_0189  \\\n",
       "ASV_1                    750                  0                504   \n",
       "ASV_2                    876                287               1511   \n",
       "ASV_3                     14                  0                238   \n",
       "ASV_4                   1123                127                716   \n",
       "ASV_5                      0                  0                 89   \n",
       "...                      ...                ...                ...   \n",
       "ASV_52160                  0                  0                  0   \n",
       "ASV_52161                  0                  0                  0   \n",
       "ASV_52162                  0                  0                  0   \n",
       "ASV_52163                  0                  0                  0   \n",
       "ASV_52164                  0                  0                  0   \n",
       "\n",
       "new_id     2020-023_SPC_0409  2020-023_SPC_0480  2020-023_SPC_0515  \\\n",
       "ASV_1                   1066               1194                  0   \n",
       "ASV_2                   1921                  4                972   \n",
       "ASV_3                      0                  0                  0   \n",
       "ASV_4                   1911                  5                  0   \n",
       "ASV_5                   2915                  0                 79   \n",
       "...                      ...                ...                ...   \n",
       "ASV_52160                  0                  0                  0   \n",
       "ASV_52161                  0                  0                  0   \n",
       "ASV_52162                  0                  0                  0   \n",
       "ASV_52163                  0                  0                  0   \n",
       "ASV_52164                  0                  0                  0   \n",
       "\n",
       "new_id     2020-023_SPC_0726  2020-023_SPC_0741  \n",
       "ASV_1                    764               3190  \n",
       "ASV_2                     43                  0  \n",
       "ASV_3                    136                  0  \n",
       "ASV_4                    493               1326  \n",
       "ASV_5                      0                  0  \n",
       "...                      ...                ...  \n",
       "ASV_52160                  0                  0  \n",
       "ASV_52161                  0                  0  \n",
       "ASV_52162                  0                  0  \n",
       "ASV_52163                  0                  0  \n",
       "ASV_52164                  0                  0  \n",
       "\n",
       "[52164 rows x 50 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BSPSPC_ASV_stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "BSPSPC_ASV_stool = pd.concat([BSPSPC_ASV_stool, BSPSPC_tax_stool_common['mASV']], axis=1)\n",
    "BSPSPC_ASV_stool.dropna(subset=['mASV'], inplace=True)\n",
    "BSPSPC_ASV_stool.set_index('mASV', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-023_BSP_0011</th>\n",
       "      <th>2020-023_BSP_0041</th>\n",
       "      <th>2020-023_BSP_0055</th>\n",
       "      <th>2020-023_BSP_0096</th>\n",
       "      <th>2020-023_BSP_0119</th>\n",
       "      <th>2020-023_BSP_0132</th>\n",
       "      <th>2020-023_BSP_0173</th>\n",
       "      <th>2020-023_BSP_0198</th>\n",
       "      <th>2020-023_BSP_0217</th>\n",
       "      <th>2020-023_BSP_0249</th>\n",
       "      <th>...</th>\n",
       "      <th>2020-023_BSP_0756</th>\n",
       "      <th>2020-023_BSP_0762</th>\n",
       "      <th>2020-023_SPC_0034</th>\n",
       "      <th>2020-023_SPC_0171</th>\n",
       "      <th>2020-023_SPC_0189</th>\n",
       "      <th>2020-023_SPC_0409</th>\n",
       "      <th>2020-023_SPC_0480</th>\n",
       "      <th>2020-023_SPC_0515</th>\n",
       "      <th>2020-023_SPC_0726</th>\n",
       "      <th>2020-023_SPC_0741</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mASV</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_1391</th>\n",
       "      <td>469</td>\n",
       "      <td>227</td>\n",
       "      <td>660</td>\n",
       "      <td>303</td>\n",
       "      <td>198</td>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>721</td>\n",
       "      <td>5370</td>\n",
       "      <td>119</td>\n",
       "      <td>...</td>\n",
       "      <td>1310</td>\n",
       "      <td>135</td>\n",
       "      <td>750</td>\n",
       "      <td>0</td>\n",
       "      <td>504</td>\n",
       "      <td>1066</td>\n",
       "      <td>1194</td>\n",
       "      <td>0</td>\n",
       "      <td>764</td>\n",
       "      <td>3190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1179</th>\n",
       "      <td>0</td>\n",
       "      <td>384</td>\n",
       "      <td>0</td>\n",
       "      <td>547</td>\n",
       "      <td>66</td>\n",
       "      <td>114</td>\n",
       "      <td>512</td>\n",
       "      <td>1198</td>\n",
       "      <td>0</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>876</td>\n",
       "      <td>287</td>\n",
       "      <td>1511</td>\n",
       "      <td>1921</td>\n",
       "      <td>4</td>\n",
       "      <td>972</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_1432</th>\n",
       "      <td>2235</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>365</td>\n",
       "      <td>305</td>\n",
       "      <td>114</td>\n",
       "      <td>1009</td>\n",
       "      <td>1214</td>\n",
       "      <td>0</td>\n",
       "      <td>287</td>\n",
       "      <td>...</td>\n",
       "      <td>1172</td>\n",
       "      <td>159</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "      <td>238</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>136</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_736</th>\n",
       "      <td>1506</td>\n",
       "      <td>0</td>\n",
       "      <td>380</td>\n",
       "      <td>456</td>\n",
       "      <td>274</td>\n",
       "      <td>38</td>\n",
       "      <td>133</td>\n",
       "      <td>823</td>\n",
       "      <td>366</td>\n",
       "      <td>376</td>\n",
       "      <td>...</td>\n",
       "      <td>1517</td>\n",
       "      <td>0</td>\n",
       "      <td>1123</td>\n",
       "      <td>127</td>\n",
       "      <td>716</td>\n",
       "      <td>1911</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>493</td>\n",
       "      <td>1326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_9133</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>235</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9004</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3382</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>89</td>\n",
       "      <td>2915</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_10245</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_6535</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_10602</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_8947</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_498</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13719 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           2020-023_BSP_0011  2020-023_BSP_0041  2020-023_BSP_0055  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                 469                227                660   \n",
       "ASV_1179                   0                384                  0   \n",
       "ASV_1432                2235                  0                  0   \n",
       "ASV_736                 1506                  0                380   \n",
       "ASV_9133                   0                  0                 53   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10245                  0                  0                  0   \n",
       "ASV_6535                   0                  0                  0   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_8947                   0                  0                  0   \n",
       "ASV_498                    0                  0                  0   \n",
       "\n",
       "           2020-023_BSP_0096  2020-023_BSP_0119  2020-023_BSP_0132  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                 303                198                114   \n",
       "ASV_1179                 547                 66                114   \n",
       "ASV_1432                 365                305                114   \n",
       "ASV_736                  456                274                 38   \n",
       "ASV_9133                   0                235                  0   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10245                  0                  0                  0   \n",
       "ASV_6535                   0                  0                  0   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_8947                   0                  0                  0   \n",
       "ASV_498                    0                  0                  0   \n",
       "\n",
       "           2020-023_BSP_0173  2020-023_BSP_0198  2020-023_BSP_0217  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                   0                721               5370   \n",
       "ASV_1179                 512               1198                  0   \n",
       "ASV_1432                1009               1214                  0   \n",
       "ASV_736                  133                823                366   \n",
       "ASV_9133                   0                  0               9004   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10245                  0                  0                  0   \n",
       "ASV_6535                   0                  0                  0   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_8947                   0                  0                  0   \n",
       "ASV_498                    0                  0                  0   \n",
       "\n",
       "           2020-023_BSP_0249  ...  2020-023_BSP_0756  2020-023_BSP_0762  \\\n",
       "mASV                          ...                                         \n",
       "ASV_1391                 119  ...               1310                135   \n",
       "ASV_1179                 127  ...                  0                  0   \n",
       "ASV_1432                 287  ...               1172                159   \n",
       "ASV_736                  376  ...               1517                  0   \n",
       "ASV_9133                   0  ...                  0               3382   \n",
       "...                      ...  ...                ...                ...   \n",
       "ASV_10245                  0  ...                  0                  0   \n",
       "ASV_6535                   0  ...                  0                  0   \n",
       "ASV_10602                  0  ...                  0                  0   \n",
       "ASV_8947                   0  ...                  0                  0   \n",
       "ASV_498                    0  ...                  0                  0   \n",
       "\n",
       "           2020-023_SPC_0034  2020-023_SPC_0171  2020-023_SPC_0189  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                 750                  0                504   \n",
       "ASV_1179                 876                287               1511   \n",
       "ASV_1432                  14                  0                238   \n",
       "ASV_736                 1123                127                716   \n",
       "ASV_9133                   0                  0                 89   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10245                  0                  0                  0   \n",
       "ASV_6535                   0                  0                  0   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_8947                   0                  0                  0   \n",
       "ASV_498                    0                  0                  0   \n",
       "\n",
       "           2020-023_SPC_0409  2020-023_SPC_0480  2020-023_SPC_0515  \\\n",
       "mASV                                                                 \n",
       "ASV_1391                1066               1194                  0   \n",
       "ASV_1179                1921                  4                972   \n",
       "ASV_1432                   0                  0                  0   \n",
       "ASV_736                 1911                  5                  0   \n",
       "ASV_9133                2915                  0                 79   \n",
       "...                      ...                ...                ...   \n",
       "ASV_10245                  0                  0                  0   \n",
       "ASV_6535                   0                  0                  0   \n",
       "ASV_10602                  0                  0                  0   \n",
       "ASV_8947                   0                  0                  0   \n",
       "ASV_498                    0                  0                  0   \n",
       "\n",
       "           2020-023_SPC_0726  2020-023_SPC_0741  \n",
       "mASV                                             \n",
       "ASV_1391                 764               3190  \n",
       "ASV_1179                  43                  0  \n",
       "ASV_1432                 136                  0  \n",
       "ASV_736                  493               1326  \n",
       "ASV_9133                   0                  0  \n",
       "...                      ...                ...  \n",
       "ASV_10245                  0                  0  \n",
       "ASV_6535                   0                  0  \n",
       "ASV_10602                  0                  0  \n",
       "ASV_8947                   0                  0  \n",
       "ASV_498                    0                  0  \n",
       "\n",
       "[13719 rows x 50 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BSPSPC_ASV_stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "#return to normal view\n",
    "BSPSPC_ASV_stool = BSPSPC_ASV_stool.T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Meta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the meta\n",
    "PSC_ASV_seren['Material'] = 'seren'\n",
    "PSC_ASV_seren['Group'] = 'PSC'\n",
    "\n",
    "PSC_ASV_stool['Material'] = 'stool'\n",
    "PSC_ASV_stool['Group'] = 'PSC'\n",
    "\n",
    "BSPSPC_ASV_seren['Material'] = 'seren'\n",
    "BSPSPC_ASV_seren['Group'] = 'HC'\n",
    "\n",
    "BSPSPC_ASV_stool['Material'] = 'stool'\n",
    "BSPSPC_ASV_stool['Group'] = 'HC'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create meta with Group and Material columns\n",
    "meta_df = pd.concat([PSC_ASV_seren[['Material', 'Group']], PSC_ASV_stool[['Material', 'Group']], BSPSPC_ASV_seren[['Material', 'Group']], BSPSPC_ASV_stool[['Material', 'Group']]], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Material</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0480_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>758 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Material Group\n",
       "new_id                              \n",
       "2020-023_PSC_0001_srn    seren   PSC\n",
       "2020-023_PSC_0006_srn    seren   PSC\n",
       "2020-023_PSC_0007_srn    seren   PSC\n",
       "2020-023_PSC_0010_srn    seren   PSC\n",
       "2020-023_PSC_0015_srn    seren   PSC\n",
       "...                        ...   ...\n",
       "2020-023_SPC_0409_stl    stool    HC\n",
       "2020-023_SPC_0480_stl    stool    HC\n",
       "2020-023_SPC_0515_stl    stool    HC\n",
       "2020-023_SPC_0726_stl    stool    HC\n",
       "2020-023_SPC_0741_stl    stool    HC\n",
       "\n",
       "[758 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "meta_df.to_csv('./results/meta_df.csv', index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Merging ASVs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "PSC_ASV_seren = PSC_ASV_seren.drop(columns = ['Material','Group'], axis=1)\n",
    "PSC_ASV_stool= PSC_ASV_stool.drop(columns = ['Material','Group'], axis=1)\n",
    "\n",
    "BSPSPC_ASV_seren= BSPSPC_ASV_seren.drop(columns = ['Material','Group'], axis=1)\n",
    "BSPSPC_ASV_stool= BSPSPC_ASV_stool.drop(columns = ['Material','Group'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create biom objects\n",
    "biom_PSC_ASV_seren = qiime2.Artifact.import_data('FeatureTable[Frequency]', PSC_ASV_seren)\n",
    "biom_PSC_ASV_stool = qiime2.Artifact.import_data('FeatureTable[Frequency]', PSC_ASV_stool)\n",
    "\n",
    "biom_BSPSPC_ASV_seren = qiime2.Artifact.import_data('FeatureTable[Frequency]', BSPSPC_ASV_seren)\n",
    "biom_BSPSPC_ASV_stool = qiime2.Artifact.import_data('FeatureTable[Frequency]', BSPSPC_ASV_stool)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./results/biom_BSPSPC_ASV_stool.qza'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#save bioms as qza\n",
    "biom_PSC_ASV_seren.save('./results/biom_PSC_ASV_seren.qza')\n",
    "biom_PSC_ASV_stool.save('./results/biom_PSC_ASV_stool.qza')\n",
    "\n",
    "biom_BSPSPC_ASV_seren.save('./results/biom_BSPSPC_ASV_seren.qza')\n",
    "biom_BSPSPC_ASV_stool.save('./results/biom_BSPSPC_ASV_stool.qza')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "PSC_ASV_seren = PSC_ASV_seren.T.rename_axis('#OTUID')\n",
    "PSC_ASV_stool = PSC_ASV_stool.T.rename_axis('#OTUID')\n",
    "BSPSPC_ASV_seren = BSPSPC_ASV_seren.T.rename_axis('#OTUID')\n",
    "BSPSPC_ASV_stool = BSPSPC_ASV_stool.T.rename_axis('#OTUID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>new_id</th>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <th>2020-023_PSC_0016_srn</th>\n",
       "      <th>2020-023_PSC_0023_srn</th>\n",
       "      <th>2020-023_PSC_0031_srn</th>\n",
       "      <th>2020-023_PSC_0032_srn</th>\n",
       "      <th>2020-023_PSC_0037_srn</th>\n",
       "      <th>...</th>\n",
       "      <th>2020-023_PSC_0752_srn</th>\n",
       "      <th>2020-023_PSC_0755_srn</th>\n",
       "      <th>2020-023_PSC_0760_srn</th>\n",
       "      <th>2020-023_PSC_0763_srn</th>\n",
       "      <th>2020-023_PSC_0764_srn</th>\n",
       "      <th>2020-023_PSC_0766_srn</th>\n",
       "      <th>2020-023_PSC_0768_srn</th>\n",
       "      <th>2020-023_PSC_0769_srn</th>\n",
       "      <th>2020-023_PSC_0775_srn</th>\n",
       "      <th>2020-023_PSC_0781_srn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#OTUID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASV_1</th>\n",
       "      <td>669</td>\n",
       "      <td>988</td>\n",
       "      <td>829</td>\n",
       "      <td>501</td>\n",
       "      <td>584</td>\n",
       "      <td>699</td>\n",
       "      <td>540</td>\n",
       "      <td>422</td>\n",
       "      <td>2621</td>\n",
       "      <td>386</td>\n",
       "      <td>...</td>\n",
       "      <td>381</td>\n",
       "      <td>974</td>\n",
       "      <td>1866</td>\n",
       "      <td>0</td>\n",
       "      <td>1590</td>\n",
       "      <td>1158</td>\n",
       "      <td>210</td>\n",
       "      <td>1043</td>\n",
       "      <td>762</td>\n",
       "      <td>1100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_2</th>\n",
       "      <td>151</td>\n",
       "      <td>83</td>\n",
       "      <td>2177</td>\n",
       "      <td>0</td>\n",
       "      <td>2938</td>\n",
       "      <td>1799</td>\n",
       "      <td>3179</td>\n",
       "      <td>0</td>\n",
       "      <td>217</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1677</td>\n",
       "      <td>85</td>\n",
       "      <td>4059</td>\n",
       "      <td>0</td>\n",
       "      <td>160</td>\n",
       "      <td>0</td>\n",
       "      <td>2652</td>\n",
       "      <td>0</td>\n",
       "      <td>1613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_3</th>\n",
       "      <td>0</td>\n",
       "      <td>407</td>\n",
       "      <td>1676</td>\n",
       "      <td>0</td>\n",
       "      <td>2696</td>\n",
       "      <td>1686</td>\n",
       "      <td>2473</td>\n",
       "      <td>0</td>\n",
       "      <td>464</td>\n",
       "      <td>15</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>136</td>\n",
       "      <td>2960</td>\n",
       "      <td>0</td>\n",
       "      <td>83</td>\n",
       "      <td>0</td>\n",
       "      <td>2380</td>\n",
       "      <td>0</td>\n",
       "      <td>2143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_4</th>\n",
       "      <td>350</td>\n",
       "      <td>463</td>\n",
       "      <td>103</td>\n",
       "      <td>166</td>\n",
       "      <td>351</td>\n",
       "      <td>269</td>\n",
       "      <td>446</td>\n",
       "      <td>212</td>\n",
       "      <td>501</td>\n",
       "      <td>127</td>\n",
       "      <td>...</td>\n",
       "      <td>96</td>\n",
       "      <td>1126</td>\n",
       "      <td>1001</td>\n",
       "      <td>0</td>\n",
       "      <td>555</td>\n",
       "      <td>247</td>\n",
       "      <td>64</td>\n",
       "      <td>78</td>\n",
       "      <td>427</td>\n",
       "      <td>421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_5</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>731</td>\n",
       "      <td>110</td>\n",
       "      <td>1180</td>\n",
       "      <td>687</td>\n",
       "      <td>1366</td>\n",
       "      <td>237</td>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>633</td>\n",
       "      <td>112</td>\n",
       "      <td>1981</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>1435</td>\n",
       "      <td>122</td>\n",
       "      <td>649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_22540</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_22541</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_22542</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_22543</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASV_22544</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22544 rows × 131 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "new_id     2020-023_PSC_0001_srn  2020-023_PSC_0006_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        669                    988   \n",
       "ASV_2                        151                     83   \n",
       "ASV_3                          0                    407   \n",
       "ASV_4                        350                    463   \n",
       "ASV_5                          0                      0   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0007_srn  2020-023_PSC_0010_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        829                    501   \n",
       "ASV_2                       2177                      0   \n",
       "ASV_3                       1676                      0   \n",
       "ASV_4                        103                    166   \n",
       "ASV_5                        731                    110   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0015_srn  2020-023_PSC_0016_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        584                    699   \n",
       "ASV_2                       2938                   1799   \n",
       "ASV_3                       2696                   1686   \n",
       "ASV_4                        351                    269   \n",
       "ASV_5                       1180                    687   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0023_srn  2020-023_PSC_0031_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        540                    422   \n",
       "ASV_2                       3179                      0   \n",
       "ASV_3                       2473                      0   \n",
       "ASV_4                        446                    212   \n",
       "ASV_5                       1366                    237   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0032_srn  2020-023_PSC_0037_srn  ...  \\\n",
       "#OTUID                                                   ...   \n",
       "ASV_1                       2621                    386  ...   \n",
       "ASV_2                        217                     11  ...   \n",
       "ASV_3                        464                     15  ...   \n",
       "ASV_4                        501                    127  ...   \n",
       "ASV_5                        121                      0  ...   \n",
       "...                          ...                    ...  ...   \n",
       "ASV_22540                      0                      0  ...   \n",
       "ASV_22541                      0                      0  ...   \n",
       "ASV_22542                      0                      0  ...   \n",
       "ASV_22543                      0                      0  ...   \n",
       "ASV_22544                      0                      0  ...   \n",
       "\n",
       "new_id     2020-023_PSC_0752_srn  2020-023_PSC_0755_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        381                    974   \n",
       "ASV_2                          0                   1677   \n",
       "ASV_3                          0                      0   \n",
       "ASV_4                         96                   1126   \n",
       "ASV_5                          0                    633   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0760_srn  2020-023_PSC_0763_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                       1866                      0   \n",
       "ASV_2                         85                   4059   \n",
       "ASV_3                        136                   2960   \n",
       "ASV_4                       1001                      0   \n",
       "ASV_5                        112                   1981   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0764_srn  2020-023_PSC_0766_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                       1590                   1158   \n",
       "ASV_2                          0                    160   \n",
       "ASV_3                          0                     83   \n",
       "ASV_4                        555                    247   \n",
       "ASV_5                          0                     79   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0768_srn  2020-023_PSC_0769_srn  \\\n",
       "#OTUID                                                    \n",
       "ASV_1                        210                   1043   \n",
       "ASV_2                          0                   2652   \n",
       "ASV_3                          0                   2380   \n",
       "ASV_4                         64                     78   \n",
       "ASV_5                          0                   1435   \n",
       "...                          ...                    ...   \n",
       "ASV_22540                      0                      0   \n",
       "ASV_22541                      0                      0   \n",
       "ASV_22542                      0                      0   \n",
       "ASV_22543                      0                      0   \n",
       "ASV_22544                      0                      0   \n",
       "\n",
       "new_id     2020-023_PSC_0775_srn  2020-023_PSC_0781_srn  \n",
       "#OTUID                                                   \n",
       "ASV_1                        762                   1100  \n",
       "ASV_2                          0                   1613  \n",
       "ASV_3                          0                   2143  \n",
       "ASV_4                        427                    421  \n",
       "ASV_5                        122                    649  \n",
       "...                          ...                    ...  \n",
       "ASV_22540                      0                      0  \n",
       "ASV_22541                      0                      0  \n",
       "ASV_22542                      0                      0  \n",
       "ASV_22543                      0                      0  \n",
       "ASV_22544                      0                      0  \n",
       "\n",
       "[22544 rows x 131 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PSC_ASV_seren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define file paths for saving the text files\n",
    "file_paths = ['./results/PSC_ASV_seren.txt', './results/PSC_ASV_stool.txt', './results/BSPSPC_ASV_seren.txt', './results/BSPSPC_ASV_stool.txt']\n",
    "\n",
    "# Save each DataFrame as a text file\n",
    "for df, file_path in zip([PSC_ASV_seren, PSC_ASV_stool, BSPSPC_ASV_seren, BSPSPC_ASV_stool], file_paths):\n",
    "    df.to_csv(file_path, sep='\\t', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom convert -i ./results/PSC_ASV_seren.txt -o ./results/PSC_ASV_seren.biom --table-type=\"OTU table\" --to-hdf5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom convert -i ./results/PSC_ASV_stool.txt -o ./results/PSC_ASV_stool.biom --table-type=\"OTU table\" --to-hdf5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom convert -i ./results/BSPSPC_ASV_seren.txt -o ./results/BSPSPC_ASV_seren.biom --table-type=\"OTU table\" --to-hdf5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom convert -i ./results/BSPSPC_ASV_stool.txt -o ./results/BSPSPC_ASV_stool.biom --table-type=\"OTU table\" --to-hdf5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## transform taxonomy files for biom\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define a function to concatenate taxonomic ranks into a single column separated by \";\"\n",
    "def combine_taxonomic_ranks(row):\n",
    "    ranks = ['Kingdom', 'Phylum', 'Class', 'Order', 'Family', 'Genus', 'Species']\n",
    "    return ';'.join(str(row[rank]) if isinstance(row[rank], str) else '' for rank in ranks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "datasets = [PSC_tax_seren, PSC_tax_stool, BSPSPC_tax_seren, BSPSPC_tax_stool]\n",
    "\n",
    "for df in datasets:\n",
    "    df['#OTUID'] = df.index\n",
    "    # Concatenate taxonomic ranks into a single column separated by \";\"\n",
    "    df['taxonomy'] = df.apply(combine_taxonomic_ranks, axis=1)\n",
    "    # Add a 'confidence' column with a default value of -1.0\n",
    "    df['confidence'] = -1.0\n",
    "    df.drop(columns=[col for col in df.columns if col not in ['#OTUID', 'taxonomy', 'confidence']], inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_paths = ['./results/PSC_tax_seren.tsv', './results/PSC_tax_stool.tsv', './results/BSPSPC_tax_seren.tsv', './results/BSPSPC_tax_stool.tsv']\n",
    "# Save each DataFrame as a TSV file\n",
    "for df, file_path in zip(datasets, file_paths):\n",
    "    df.to_csv(file_path, sep='\\t', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom add-metadata -i ./results/PSC_ASV_seren.biom -o ./results/PSC_ASV_seren_taxonomy.biom --observation-metadata-fp ./results/PSC_tax_seren.tsv --sc-separated taxonomy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom add-metadata -i ./results/PSC_ASV_stool.biom -o ./results/PSC_ASV_stool_taxonomy.biom --observation-metadata-fp ./results/PSC_tax_stool.tsv --sc-separated taxonomy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom add-metadata -i ./results/BSPSPC_ASV_seren.biom -o ./results/BSPSPC_ASV_seren_taxonomy.biom --observation-metadata-fp ./results/BSPSPC_tax_seren.tsv --sc-separated taxonomy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "!biom add-metadata -i ./results/BSPSPC_ASV_stool.biom -o ./results/BSPSPC_ASV_stool_taxonomy.biom --observation-metadata-fp ./results/BSPSPC_tax_stool.tsv --sc-separated taxonomy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### preparing .qza files "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mImported ./results/PSC_ASV_seren_taxonomy.biom as BIOMV210Format to ./results/PSC_ASV_seren_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime tools import \\\n",
    "  --input-path ./results/PSC_ASV_seren_taxonomy.biom \\\n",
    "  --type 'FeatureTable[Frequency]' \\\n",
    "  --input-format BIOMV210Format \\\n",
    "  --output-path ./results/PSC_ASV_seren_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mImported ./results/PSC_ASV_stool_taxonomy.biom as BIOMV210Format to ./results/PSC_ASV_stool_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime tools import \\\n",
    "  --input-path ./results/PSC_ASV_stool_taxonomy.biom \\\n",
    "  --type 'FeatureTable[Frequency]' \\\n",
    "  --input-format BIOMV210Format \\\n",
    "  --output-path ./results/PSC_ASV_stool_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mImported ./results/BSPSPC_ASV_seren_taxonomy.biom as BIOMV210Format to ./results/BSPSPC_ASV_seren_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime tools import \\\n",
    "  --input-path ./results/BSPSPC_ASV_seren_taxonomy.biom \\\n",
    "  --type 'FeatureTable[Frequency]' \\\n",
    "  --input-format BIOMV210Format \\\n",
    "  --output-path ./results/BSPSPC_ASV_seren_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mImported ./results/BSPSPC_ASV_stool_taxonomy.biom as BIOMV210Format to ./results/BSPSPC_ASV_stool_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime tools import \\\n",
    "  --input-path ./results/BSPSPC_ASV_stool_taxonomy.biom \\\n",
    "  --type 'FeatureTable[Frequency]' \\\n",
    "  --input-format BIOMV210Format \\\n",
    "  --output-path ./results/BSPSPC_ASV_stool_taxonomy.qza"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_BSPSPC_ASV_seren_taxonomy.qza\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# Normalization\n",
    "!qiime feature-table rarefy \\\n",
    "  --i-table ./results/BSPSPC_ASV_seren_taxonomy.qza \\\n",
    "  --p-sampling-depth 5000 \\\n",
    "  --o-rarefied-table ./results/norm_BSPSPC_ASV_seren_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_BSPSPC_ASV_stool_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# Normalization\n",
    "!qiime feature-table rarefy \\\n",
    "  --i-table ./results/BSPSPC_ASV_stool_taxonomy.qza \\\n",
    "  --p-sampling-depth 10000 \\\n",
    "  --o-rarefied-table ./results/norm_BSPSPC_ASV_stool_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_PSC_ASV_seren_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# Normalization\n",
    "!qiime feature-table rarefy \\\n",
    "  --i-table ./results/PSC_ASV_seren_taxonomy.qza \\\n",
    "  --p-sampling-depth 2500 \\\n",
    "  --o-rarefied-table ./results/norm_PSC_ASV_seren_taxonomy.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_PSC_ASV_stool_taxonomy.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "# Normalization\n",
    "!qiime feature-table rarefy \\\n",
    "  --i-table ./results/PSC_ASV_stool_taxonomy.qza \\\n",
    "  --p-sampling-depth 10000 \\\n",
    "  --o-rarefied-table ./results/norm_PSC_ASV_stool_taxonomy.qza"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### merging!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_merged_ASV_abundances.qza\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table merge \\\n",
    "  --i-tables ./results/norm_PSC_ASV_seren_taxonomy.qza \\\n",
    "  --i-tables ./results/norm_PSC_ASV_stool_taxonomy.qza \\\n",
    "  --i-tables ./results/norm_BSPSPC_ASV_seren_taxonomy.qza \\\n",
    "  --i-tables ./results/norm_BSPSPC_ASV_stool_taxonomy.qza \\\n",
    "  --o-merged-table ./results/norm_merged_ASV_abundances.qza"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## merging stool and seren separatly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_merged_ASV_abundances_seren.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table merge \\\n",
    "  --i-tables ./results/norm_PSC_ASV_seren_taxonomy.qza \\\n",
    "  --i-tables ./results/norm_BSPSPC_ASV_seren_taxonomy.qza \\\n",
    "  --o-merged-table ./results/norm_merged_ASV_abundances_seren.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[Frequency] to: ./results/norm_merged_ASV_abundances_stool.qza\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table merge \\\n",
    "  --i-tables ./results/norm_PSC_ASV_stool_taxonomy.qza \\\n",
    "  --i-tables ./results/norm_BSPSPC_ASV_stool_taxonomy.qza \\\n",
    "  --o-merged-table ./results/norm_merged_ASV_abundances_stool.qza"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### for seren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load rarefied ab table from the Qiime artifact\n",
    "ab = Artifact.load('./results/norm_merged_ASV_abundances_seren.qza')\n",
    "\n",
    "# Convert the PCoA results to a pandas DataFrame\n",
    "ab = ab.view(pd.DataFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Low count filter: \tminimum count 4 in 10% of samples\n",
    "# Calculate the count threshold for the low count filter\n",
    "min_count_threshold = 4\n",
    "min_samples_threshold = len(ab) * 0.1\n",
    "\n",
    "# Select taxa with count >= min_count_threshold in at least min_samples_threshold samples\n",
    "ab = ab.loc[:, (ab >= min_count_threshold).sum(axis=0) >= min_samples_threshold]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ASV_1</th>\n",
       "      <th>ASV_10</th>\n",
       "      <th>ASV_100</th>\n",
       "      <th>ASV_102</th>\n",
       "      <th>ASV_103</th>\n",
       "      <th>ASV_104</th>\n",
       "      <th>ASV_105</th>\n",
       "      <th>ASV_106</th>\n",
       "      <th>ASV_107</th>\n",
       "      <th>ASV_109</th>\n",
       "      <th>...</th>\n",
       "      <th>ASV_9</th>\n",
       "      <th>ASV_90</th>\n",
       "      <th>ASV_91</th>\n",
       "      <th>ASV_92</th>\n",
       "      <th>ASV_93</th>\n",
       "      <th>ASV_94</th>\n",
       "      <th>ASV_95</th>\n",
       "      <th>ASV_96</th>\n",
       "      <th>ASV_97</th>\n",
       "      <th>ASV_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <td>156.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>...</td>\n",
       "      <td>47.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <td>200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <td>135.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <td>286.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>157.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <td>71.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>40.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_srn</th>\n",
       "      <td>205.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0480_srn</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_srn</th>\n",
       "      <td>269.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_srn</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_srn</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 125 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       ASV_1  ASV_10  ASV_100  ASV_102  ASV_103  ASV_104  \\\n",
       "2020-023_PSC_0001_srn  156.0    23.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_PSC_0006_srn  200.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_PSC_0007_srn  135.0    14.0      0.0      0.0      0.0     11.0   \n",
       "2020-023_PSC_0010_srn  286.0    15.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_PSC_0015_srn   71.0     0.0      0.0      0.0      0.0      0.0   \n",
       "...                      ...     ...      ...      ...      ...      ...   \n",
       "2020-023_SPC_0409_srn  205.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0480_srn    0.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0515_srn  269.0    76.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0726_srn    0.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0741_srn   12.0     3.0      0.0      0.0      0.0     99.0   \n",
       "\n",
       "                       ASV_105  ASV_106  ASV_107  ASV_109  ...  ASV_9  ASV_90  \\\n",
       "2020-023_PSC_0001_srn      0.0      0.0      1.0     18.0  ...   47.0    37.0   \n",
       "2020-023_PSC_0006_srn      0.0      0.0      0.0      0.0  ...   18.0     0.0   \n",
       "2020-023_PSC_0007_srn      0.0      6.0      0.0      0.0  ...   12.0     0.0   \n",
       "2020-023_PSC_0010_srn      0.0      0.0      6.0      0.0  ...  157.0     0.0   \n",
       "2020-023_PSC_0015_srn      0.0      0.0      3.0      0.0  ...   40.0    20.0   \n",
       "...                        ...      ...      ...      ...  ...    ...     ...   \n",
       "2020-023_SPC_0409_srn      0.0      0.0      0.0      0.0  ...    0.0     0.0   \n",
       "2020-023_SPC_0480_srn      0.0      0.0      0.0      0.0  ...    0.0     0.0   \n",
       "2020-023_SPC_0515_srn      0.0      0.0      0.0      0.0  ...    0.0     0.0   \n",
       "2020-023_SPC_0726_srn      0.0      0.0      0.0      0.0  ...    0.0     0.0   \n",
       "2020-023_SPC_0741_srn     33.0      0.0      0.0      0.0  ...    0.0     0.0   \n",
       "\n",
       "                       ASV_91  ASV_92  ASV_93  ASV_94  ASV_95  ASV_96  ASV_97  \\\n",
       "2020-023_PSC_0001_srn     0.0     0.0     0.0    49.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0006_srn   119.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0007_srn     0.0     2.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0010_srn     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0015_srn    13.0    20.0     0.0     0.0     0.0     0.0     0.0   \n",
       "...                       ...     ...     ...     ...     ...     ...     ...   \n",
       "2020-023_SPC_0409_srn     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0480_srn     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0515_srn     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0726_srn     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0741_srn     0.0     0.0     0.0    56.0     0.0     0.0     0.0   \n",
       "\n",
       "                       ASV_99  \n",
       "2020-023_PSC_0001_srn     0.0  \n",
       "2020-023_PSC_0006_srn     0.0  \n",
       "2020-023_PSC_0007_srn     0.0  \n",
       "2020-023_PSC_0010_srn    16.0  \n",
       "2020-023_PSC_0015_srn     0.0  \n",
       "...                       ...  \n",
       "2020-023_SPC_0409_srn     0.0  \n",
       "2020-023_SPC_0480_srn     0.0  \n",
       "2020-023_SPC_0515_srn     0.0  \n",
       "2020-023_SPC_0726_srn     0.0  \n",
       "2020-023_SPC_0741_srn     0.0  \n",
       "\n",
       "[161 rows x 125 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Low variance filter: \t5% based on inter-quantile rang\n",
    "# Calculate the 10th and 90th percentile for each taxon\n",
    "percentiles = ab.quantile([0.05, 0.95])\n",
    "\n",
    "# Calculate the inter-quantile range (IQR) for each taxon\n",
    "iqr = percentiles.loc[0.95] - percentiles.loc[0.05]\n",
    "\n",
    "# Filter out taxa with IQR < 5% of the range\n",
    "variance_threshold = 0.1 * (ab.max() - ab.min())\n",
    "ab = ab.loc[:, iqr >= variance_threshold]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ASV_1</th>\n",
       "      <th>ASV_10</th>\n",
       "      <th>ASV_102</th>\n",
       "      <th>ASV_105</th>\n",
       "      <th>ASV_106</th>\n",
       "      <th>ASV_107</th>\n",
       "      <th>ASV_11</th>\n",
       "      <th>ASV_110</th>\n",
       "      <th>ASV_111</th>\n",
       "      <th>ASV_113</th>\n",
       "      <th>...</th>\n",
       "      <th>ASV_85</th>\n",
       "      <th>ASV_89</th>\n",
       "      <th>ASV_9</th>\n",
       "      <th>ASV_91</th>\n",
       "      <th>ASV_92</th>\n",
       "      <th>ASV_93</th>\n",
       "      <th>ASV_94</th>\n",
       "      <th>ASV_95</th>\n",
       "      <th>ASV_96</th>\n",
       "      <th>ASV_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <td>156.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <td>200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <td>135.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <td>286.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <td>71.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_srn</th>\n",
       "      <td>205.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0480_srn</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_srn</th>\n",
       "      <td>269.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_srn</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_srn</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 95 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       ASV_1  ASV_10  ASV_102  ASV_105  ASV_106  ASV_107  \\\n",
       "2020-023_PSC_0001_srn  156.0    23.0      0.0      0.0      0.0      1.0   \n",
       "2020-023_PSC_0006_srn  200.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_PSC_0007_srn  135.0    14.0      0.0      0.0      6.0      0.0   \n",
       "2020-023_PSC_0010_srn  286.0    15.0      0.0      0.0      0.0      6.0   \n",
       "2020-023_PSC_0015_srn   71.0     0.0      0.0      0.0      0.0      3.0   \n",
       "...                      ...     ...      ...      ...      ...      ...   \n",
       "2020-023_SPC_0409_srn  205.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0480_srn    0.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0515_srn  269.0    76.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0726_srn    0.0     0.0      0.0      0.0      0.0      0.0   \n",
       "2020-023_SPC_0741_srn   12.0     3.0      0.0     33.0      0.0      0.0   \n",
       "\n",
       "                       ASV_11  ASV_110  ASV_111  ASV_113  ...  ASV_85  ASV_89  \\\n",
       "2020-023_PSC_0001_srn     0.0      0.0      0.0      0.0  ...     0.0    15.0   \n",
       "2020-023_PSC_0006_srn    75.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "2020-023_PSC_0007_srn     8.0      7.0      0.0      0.0  ...     0.0     4.0   \n",
       "2020-023_PSC_0010_srn     0.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "2020-023_PSC_0015_srn    13.0      0.0      0.0     31.0  ...     0.0     3.0   \n",
       "...                       ...      ...      ...      ...  ...     ...     ...   \n",
       "2020-023_SPC_0409_srn     0.0    187.0      0.0    105.0  ...     0.0     0.0   \n",
       "2020-023_SPC_0480_srn     0.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "2020-023_SPC_0515_srn     0.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "2020-023_SPC_0726_srn     0.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "2020-023_SPC_0741_srn     0.0      0.0      0.0      0.0  ...     0.0     0.0   \n",
       "\n",
       "                       ASV_9  ASV_91  ASV_92  ASV_93  ASV_94  ASV_95  ASV_96  \\\n",
       "2020-023_PSC_0001_srn   47.0     0.0     0.0     0.0    49.0     0.0     0.0   \n",
       "2020-023_PSC_0006_srn   18.0   119.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0007_srn   12.0     0.0     2.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0010_srn  157.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_PSC_0015_srn   40.0    13.0    20.0     0.0     0.0     0.0     0.0   \n",
       "...                      ...     ...     ...     ...     ...     ...     ...   \n",
       "2020-023_SPC_0409_srn    0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0480_srn    0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0515_srn    0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0726_srn    0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0741_srn    0.0     0.0     0.0     0.0    56.0     0.0     0.0   \n",
       "\n",
       "                       ASV_99  \n",
       "2020-023_PSC_0001_srn     0.0  \n",
       "2020-023_PSC_0006_srn     0.0  \n",
       "2020-023_PSC_0007_srn     0.0  \n",
       "2020-023_PSC_0010_srn    16.0  \n",
       "2020-023_PSC_0015_srn     0.0  \n",
       "...                       ...  \n",
       "2020-023_SPC_0409_srn     0.0  \n",
       "2020-023_SPC_0480_srn     0.0  \n",
       "2020-023_SPC_0515_srn     0.0  \n",
       "2020-023_SPC_0726_srn     0.0  \n",
       "2020-023_SPC_0741_srn     0.0  \n",
       "\n",
       "[161 rows x 95 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./results/norm_merged_ASV_abundances_filtered_seren.qza'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab = qiime2.Artifact.import_data('FeatureTable[Frequency]', ab)\n",
    "ab.save('./results/norm_merged_ASV_abundances_filtered_seren.qza')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load rarefied and relative ab table from the Qiime artifact\n",
    "ab = Artifact.load('./results/norm_merged_ASV_abundances_filtered_seren.qza')\n",
    "\n",
    "# Convert to a pandas DataFrame\n",
    "ab = ab.view(pd.DataFrame)\n",
    "ab.to_csv('./results/norm_merged_ASV_abundances_filtered_seren.csv', index = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### for stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load rarefied ab table from the Qiime artifact\n",
    "ab = Artifact.load('./results/norm_merged_ASV_abundances_stool.qza')\n",
    "\n",
    "# Convert the PCoA results to a pandas DataFrame\n",
    "ab = ab.view(pd.DataFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Low count filter: \tminimum count 4 in 20% of samples\n",
    "# Calculate the count threshold for the low count filter\n",
    "min_count_threshold = 4\n",
    "min_samples_threshold = len(ab) * 0.1\n",
    "\n",
    "# Select taxa with count >= min_count_threshold in at least min_samples_threshold samples\n",
    "ab = ab.loc[:, (ab >= min_count_threshold).sum(axis=0) >= min_samples_threshold]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ASV_1</th>\n",
       "      <th>ASV_10</th>\n",
       "      <th>ASV_100</th>\n",
       "      <th>ASV_1005</th>\n",
       "      <th>ASV_101</th>\n",
       "      <th>ASV_1015</th>\n",
       "      <th>ASV_103</th>\n",
       "      <th>ASV_104</th>\n",
       "      <th>ASV_1041</th>\n",
       "      <th>ASV_106</th>\n",
       "      <th>...</th>\n",
       "      <th>ASV_918</th>\n",
       "      <th>ASV_919</th>\n",
       "      <th>ASV_92</th>\n",
       "      <th>ASV_93</th>\n",
       "      <th>ASV_94</th>\n",
       "      <th>ASV_95</th>\n",
       "      <th>ASV_96</th>\n",
       "      <th>ASV_97</th>\n",
       "      <th>ASV_971</th>\n",
       "      <th>ASV_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_stl</th>\n",
       "      <td>87.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0002_stl</th>\n",
       "      <td>945.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2076.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0003_stl</th>\n",
       "      <td>139.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0005_stl</th>\n",
       "      <td>378.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_stl</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0189_stl</th>\n",
       "      <td>287.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>787.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>197.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>406.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>1705.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>560 rows × 287 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        ASV_1  ASV_10  ASV_100  ASV_1005  ASV_101  ASV_1015  \\\n",
       "2020-023_PSC_0001_stl    87.0     0.0     51.0       0.0      3.0       0.0   \n",
       "2020-023_PSC_0002_stl   945.0     0.0      0.0       0.0      0.0       0.0   \n",
       "2020-023_PSC_0003_stl   139.0     0.0      7.0       0.0     16.0       0.0   \n",
       "2020-023_PSC_0005_stl   378.0    12.0      0.0       0.0     13.0       0.0   \n",
       "2020-023_PSC_0006_stl     8.0     0.0     20.0       0.0      5.0       0.0   \n",
       "...                       ...     ...      ...       ...      ...       ...   \n",
       "2020-023_SPC_0189_stl   287.0   138.0      0.0       0.0      0.0       0.0   \n",
       "2020-023_SPC_0409_stl   197.0     0.0      0.0       0.0      0.0       7.0   \n",
       "2020-023_SPC_0515_stl     0.0     0.0      0.0       0.0      0.0       0.0   \n",
       "2020-023_SPC_0726_stl   406.0     0.0      0.0       0.0      5.0       0.0   \n",
       "2020-023_SPC_0741_stl  1705.0     0.0      0.0       0.0      0.0       0.0   \n",
       "\n",
       "                       ASV_103  ASV_104  ASV_1041  ASV_106  ...  ASV_918  \\\n",
       "2020-023_PSC_0001_stl     91.0      0.0       0.0      0.0  ...      0.0   \n",
       "2020-023_PSC_0002_stl      0.0      0.0       0.0      0.0  ...      0.0   \n",
       "2020-023_PSC_0003_stl     43.0      0.0       0.0     56.0  ...      0.0   \n",
       "2020-023_PSC_0005_stl      0.0      0.0       0.0      0.0  ...      6.0   \n",
       "2020-023_PSC_0006_stl      0.0      0.0       9.0      0.0  ...      9.0   \n",
       "...                        ...      ...       ...      ...  ...      ...   \n",
       "2020-023_SPC_0189_stl    787.0     10.0       0.0    156.0  ...      0.0   \n",
       "2020-023_SPC_0409_stl      0.0      0.0       0.0      0.0  ...      0.0   \n",
       "2020-023_SPC_0515_stl      3.0      4.0       0.0      1.0  ...      0.0   \n",
       "2020-023_SPC_0726_stl      0.0     30.0       0.0      0.0  ...      0.0   \n",
       "2020-023_SPC_0741_stl    386.0      0.0       0.0     17.0  ...      0.0   \n",
       "\n",
       "                       ASV_919  ASV_92  ASV_93  ASV_94  ASV_95  ASV_96  \\\n",
       "2020-023_PSC_0001_stl      0.0     0.0    21.0    12.0     0.0     0.0   \n",
       "2020-023_PSC_0002_stl      0.0     0.0     0.0     0.0     0.0  2076.0   \n",
       "2020-023_PSC_0003_stl      0.0     0.0     0.0    16.0     0.0     0.0   \n",
       "2020-023_PSC_0005_stl      0.0     0.0     0.0     9.0     0.0     2.0   \n",
       "2020-023_PSC_0006_stl      0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "...                        ...     ...     ...     ...     ...     ...   \n",
       "2020-023_SPC_0189_stl      0.0     0.0     0.0    18.0     0.0     0.0   \n",
       "2020-023_SPC_0409_stl      0.0     0.0     0.0     0.0     0.0    18.0   \n",
       "2020-023_SPC_0515_stl      0.0    12.0     0.0    76.0     0.0   137.0   \n",
       "2020-023_SPC_0726_stl      0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "2020-023_SPC_0741_stl      0.0     0.0     0.0     0.0     0.0   307.0   \n",
       "\n",
       "                       ASV_97  ASV_971  ASV_99  \n",
       "2020-023_PSC_0001_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0002_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0003_stl     0.0      0.0    68.0  \n",
       "2020-023_PSC_0005_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0006_stl     0.0      0.0     0.0  \n",
       "...                       ...      ...     ...  \n",
       "2020-023_SPC_0189_stl     0.0      0.0     0.0  \n",
       "2020-023_SPC_0409_stl     0.0      0.0   150.0  \n",
       "2020-023_SPC_0515_stl     0.0      0.0     0.0  \n",
       "2020-023_SPC_0726_stl     0.0      0.0     8.0  \n",
       "2020-023_SPC_0741_stl     0.0      0.0     0.0  \n",
       "\n",
       "[560 rows x 287 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Low variance filter: \t5% based on inter-quantile rang\n",
    "# Calculate the 10th and 90th percentile for each taxon\n",
    "percentiles = ab.quantile([0.05, 0.95])\n",
    "\n",
    "# Calculate the inter-quantile range (IQR) for each taxon\n",
    "iqr = percentiles.loc[0.95] - percentiles.loc[0.05]\n",
    "\n",
    "# Filter out taxa with IQR < 5% of the range\n",
    "variance_threshold = 0.1 * (ab.max() - ab.min())\n",
    "ab = ab.loc[:, iqr >= variance_threshold]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ASV_1</th>\n",
       "      <th>ASV_10</th>\n",
       "      <th>ASV_1005</th>\n",
       "      <th>ASV_101</th>\n",
       "      <th>ASV_1041</th>\n",
       "      <th>ASV_106</th>\n",
       "      <th>ASV_109</th>\n",
       "      <th>ASV_11</th>\n",
       "      <th>ASV_110</th>\n",
       "      <th>ASV_1119</th>\n",
       "      <th>...</th>\n",
       "      <th>ASV_893</th>\n",
       "      <th>ASV_898</th>\n",
       "      <th>ASV_9</th>\n",
       "      <th>ASV_90</th>\n",
       "      <th>ASV_918</th>\n",
       "      <th>ASV_92</th>\n",
       "      <th>ASV_93</th>\n",
       "      <th>ASV_95</th>\n",
       "      <th>ASV_971</th>\n",
       "      <th>ASV_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_stl</th>\n",
       "      <td>87.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0002_stl</th>\n",
       "      <td>945.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0003_stl</th>\n",
       "      <td>139.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0005_stl</th>\n",
       "      <td>378.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_stl</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0189_stl</th>\n",
       "      <td>287.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>156.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>197.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>406.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>1705.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>560 rows × 158 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        ASV_1  ASV_10  ASV_1005  ASV_101  ASV_1041  ASV_106  \\\n",
       "2020-023_PSC_0001_stl    87.0     0.0       0.0      3.0       0.0      0.0   \n",
       "2020-023_PSC_0002_stl   945.0     0.0       0.0      0.0       0.0      0.0   \n",
       "2020-023_PSC_0003_stl   139.0     0.0       0.0     16.0       0.0     56.0   \n",
       "2020-023_PSC_0005_stl   378.0    12.0       0.0     13.0       0.0      0.0   \n",
       "2020-023_PSC_0006_stl     8.0     0.0       0.0      5.0       9.0      0.0   \n",
       "...                       ...     ...       ...      ...       ...      ...   \n",
       "2020-023_SPC_0189_stl   287.0   138.0       0.0      0.0       0.0    156.0   \n",
       "2020-023_SPC_0409_stl   197.0     0.0       0.0      0.0       0.0      0.0   \n",
       "2020-023_SPC_0515_stl     0.0     0.0       0.0      0.0       0.0      1.0   \n",
       "2020-023_SPC_0726_stl   406.0     0.0       0.0      5.0       0.0      0.0   \n",
       "2020-023_SPC_0741_stl  1705.0     0.0       0.0      0.0       0.0     17.0   \n",
       "\n",
       "                       ASV_109  ASV_11  ASV_110  ASV_1119  ...  ASV_893  \\\n",
       "2020-023_PSC_0001_stl      0.0     0.0      0.0       0.0  ...     25.0   \n",
       "2020-023_PSC_0002_stl      0.0    23.0      0.0       0.0  ...      0.0   \n",
       "2020-023_PSC_0003_stl      0.0    60.0     27.0       0.0  ...      0.0   \n",
       "2020-023_PSC_0005_stl      0.0     0.0      0.0       0.0  ...      0.0   \n",
       "2020-023_PSC_0006_stl      0.0    23.0      0.0       5.0  ...      6.0   \n",
       "...                        ...     ...      ...       ...  ...      ...   \n",
       "2020-023_SPC_0189_stl      0.0     0.0      0.0       0.0  ...      0.0   \n",
       "2020-023_SPC_0409_stl      0.0     0.0      0.0       0.0  ...      0.0   \n",
       "2020-023_SPC_0515_stl      0.0   689.0      0.0       0.0  ...      0.0   \n",
       "2020-023_SPC_0726_stl      0.0     0.0    244.0       0.0  ...      0.0   \n",
       "2020-023_SPC_0741_stl      0.0     0.0     40.0       0.0  ...      0.0   \n",
       "\n",
       "                       ASV_898  ASV_9  ASV_90  ASV_918  ASV_92  ASV_93  \\\n",
       "2020-023_PSC_0001_stl      0.0   29.0     0.0      0.0     0.0    21.0   \n",
       "2020-023_PSC_0002_stl      0.0  218.0     0.0      0.0     0.0     0.0   \n",
       "2020-023_PSC_0003_stl      0.0    0.0     0.0      0.0     0.0     0.0   \n",
       "2020-023_PSC_0005_stl      0.0   25.0     0.0      6.0     0.0     0.0   \n",
       "2020-023_PSC_0006_stl      7.0    0.0     0.0      9.0     0.0     0.0   \n",
       "...                        ...    ...     ...      ...     ...     ...   \n",
       "2020-023_SPC_0189_stl      0.0    0.0     0.0      0.0     0.0     0.0   \n",
       "2020-023_SPC_0409_stl      0.0    0.0     0.0      0.0     0.0     0.0   \n",
       "2020-023_SPC_0515_stl      0.0  116.0     0.0      0.0    12.0     0.0   \n",
       "2020-023_SPC_0726_stl      0.0    0.0     0.0      0.0     0.0     0.0   \n",
       "2020-023_SPC_0741_stl      0.0    0.0     0.0      0.0     0.0     0.0   \n",
       "\n",
       "                       ASV_95  ASV_971  ASV_99  \n",
       "2020-023_PSC_0001_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0002_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0003_stl     0.0      0.0    68.0  \n",
       "2020-023_PSC_0005_stl     0.0      0.0     0.0  \n",
       "2020-023_PSC_0006_stl     0.0      0.0     0.0  \n",
       "...                       ...      ...     ...  \n",
       "2020-023_SPC_0189_stl     0.0      0.0     0.0  \n",
       "2020-023_SPC_0409_stl     0.0      0.0   150.0  \n",
       "2020-023_SPC_0515_stl     0.0      0.0     0.0  \n",
       "2020-023_SPC_0726_stl     0.0      0.0     8.0  \n",
       "2020-023_SPC_0741_stl     0.0      0.0     0.0  \n",
       "\n",
       "[560 rows x 158 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./results/norm_merged_ASV_abundances_filtered_stool.qza'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab = qiime2.Artifact.import_data('FeatureTable[Frequency]', ab)\n",
    "ab.save('./results/norm_merged_ASV_abundances_filtered_stool.qza')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load rarefied and relative ab table from the Qiime artifact\n",
    "ab = Artifact.load('./results/norm_merged_ASV_abundances_filtered_stool.qza')\n",
    "\n",
    "# Convert to a pandas DataFrame\n",
    "ab = ab.view(pd.DataFrame)\n",
    "ab.to_csv('./results/norm_merged_ASV_abundances_filtered_stool.csv', index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ab = pd.read_csv('./results/norm_merged_ASV_abundances_filtered_stool.csv',index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ASV_10033</th>\n",
       "      <th>ASV_10172</th>\n",
       "      <th>ASV_10205</th>\n",
       "      <th>ASV_10230</th>\n",
       "      <th>ASV_10262</th>\n",
       "      <th>ASV_10278</th>\n",
       "      <th>ASV_10282</th>\n",
       "      <th>ASV_10522</th>\n",
       "      <th>ASV_10545</th>\n",
       "      <th>ASV_10589</th>\n",
       "      <th>...</th>\n",
       "      <th>ASV_9535</th>\n",
       "      <th>ASV_9597</th>\n",
       "      <th>ASV_9745</th>\n",
       "      <th>ASV_9817</th>\n",
       "      <th>ASV_9841</th>\n",
       "      <th>ASV_9845</th>\n",
       "      <th>ASV_9854</th>\n",
       "      <th>ASV_9944</th>\n",
       "      <th>ASV_9968</th>\n",
       "      <th>ASV_9987</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_stl</th>\n",
       "      <td>78.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0002_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0003_stl</th>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0005_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0189_stl</th>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>553 rows × 191 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       ASV_10033  ASV_10172  ASV_10205  ASV_10230  ASV_10262  \\\n",
       "2020-023_PSC_0001_stl       78.0        0.0       13.0       86.0       18.0   \n",
       "2020-023_PSC_0002_stl        0.0        0.0        7.0        0.0        4.0   \n",
       "2020-023_PSC_0003_stl       29.0        0.0        0.0       44.0        0.0   \n",
       "2020-023_PSC_0005_stl        0.0        0.0        0.0        0.0       14.0   \n",
       "2020-023_PSC_0006_stl        0.0       25.0        0.0        0.0        0.0   \n",
       "...                          ...        ...        ...        ...        ...   \n",
       "2020-023_SPC_0189_stl        7.0        3.0        0.0       16.0        0.0   \n",
       "2020-023_SPC_0409_stl       14.0        0.0        0.0        0.0        0.0   \n",
       "2020-023_SPC_0515_stl        0.0        0.0       68.0        2.0      139.0   \n",
       "2020-023_SPC_0726_stl       25.0        0.0       13.0       32.0       33.0   \n",
       "2020-023_SPC_0741_stl        0.0       13.0        0.0        0.0        0.0   \n",
       "\n",
       "                       ASV_10278  ASV_10282  ASV_10522  ASV_10545  ASV_10589  \\\n",
       "2020-023_PSC_0001_stl        0.0       37.0        0.0        0.0        0.0   \n",
       "2020-023_PSC_0002_stl        0.0        0.0        0.0        0.0        0.0   \n",
       "2020-023_PSC_0003_stl        0.0        0.0        0.0       94.0        0.0   \n",
       "2020-023_PSC_0005_stl        0.0        0.0        0.0        0.0       10.0   \n",
       "2020-023_PSC_0006_stl        0.0        0.0       27.0        0.0        0.0   \n",
       "...                          ...        ...        ...        ...        ...   \n",
       "2020-023_SPC_0189_stl       11.0       15.0       14.0        0.0        0.0   \n",
       "2020-023_SPC_0409_stl        5.0        0.0        0.0       14.0        2.0   \n",
       "2020-023_SPC_0515_stl        0.0        0.0        8.0        0.0       10.0   \n",
       "2020-023_SPC_0726_stl        0.0        0.0        0.0        0.0       66.0   \n",
       "2020-023_SPC_0741_stl       32.0       37.0        0.0        0.0        0.0   \n",
       "\n",
       "                       ...  ASV_9535  ASV_9597  ASV_9745  ASV_9817  ASV_9841  \\\n",
       "2020-023_PSC_0001_stl  ...       0.0       0.0       0.0       0.0      78.0   \n",
       "2020-023_PSC_0002_stl  ...       0.0       0.0       0.0       0.0       0.0   \n",
       "2020-023_PSC_0003_stl  ...       0.0       0.0       0.0       0.0      42.0   \n",
       "2020-023_PSC_0005_stl  ...       0.0       0.0       0.0       0.0       0.0   \n",
       "2020-023_PSC_0006_stl  ...      18.0       0.0       0.0       0.0       9.0   \n",
       "...                    ...       ...       ...       ...       ...       ...   \n",
       "2020-023_SPC_0189_stl  ...       9.0       0.0       0.0       8.0       0.0   \n",
       "2020-023_SPC_0409_stl  ...       0.0       0.0       0.0       0.0       8.0   \n",
       "2020-023_SPC_0515_stl  ...       0.0      33.0       0.0       0.0       6.0   \n",
       "2020-023_SPC_0726_stl  ...      29.0       0.0       0.0       0.0       6.0   \n",
       "2020-023_SPC_0741_stl  ...       0.0      21.0       0.0       7.0       0.0   \n",
       "\n",
       "                       ASV_9845  ASV_9854  ASV_9944  ASV_9968  ASV_9987  \n",
       "2020-023_PSC_0001_stl       0.0      55.0      15.0       0.0       0.0  \n",
       "2020-023_PSC_0002_stl       0.0       0.0       0.0       0.0       0.0  \n",
       "2020-023_PSC_0003_stl       0.0       0.0      91.0       0.0       0.0  \n",
       "2020-023_PSC_0005_stl       0.0       0.0       0.0      18.0       0.0  \n",
       "2020-023_PSC_0006_stl       0.0      35.0      22.0       0.0       0.0  \n",
       "...                         ...       ...       ...       ...       ...  \n",
       "2020-023_SPC_0189_stl       0.0       0.0       0.0       0.0       0.0  \n",
       "2020-023_SPC_0409_stl       0.0       4.0       0.0       0.0       0.0  \n",
       "2020-023_SPC_0515_stl       0.0      15.0       0.0      13.0       0.0  \n",
       "2020-023_SPC_0726_stl       0.0       0.0     126.0       0.0      29.0  \n",
       "2020-023_SPC_0741_stl       0.0       0.0     100.0      49.0       0.0  \n",
       "\n",
       "[553 rows x 191 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "507"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ab.index.str.contains('PSC').sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### relative frequencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[RelativeFrequency] to: ./results/rel_norm_merged_ASV_abundances.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table relative-frequency \\\n",
    "--i-table ./results/norm_merged_ASV_abundances.qza \\\n",
    "--o-relative-frequency-table ./results/rel_norm_merged_ASV_abundances.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[RelativeFrequency] to: ./results/rel_norm_merged_ASV_abundances_seren.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table relative-frequency \\\n",
    "--i-table ./results/norm_merged_ASV_abundances_seren.qza \\\n",
    "--o-relative-frequency-table ./results/rel_norm_merged_ASV_abundances_seren.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved FeatureTable[RelativeFrequency] to: ./results/rel_norm_merged_ASV_abundances_stool.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime feature-table relative-frequency \\\n",
    "--i-table ./results/norm_merged_ASV_abundances_stool.qza \\\n",
    "--o-relative-frequency-table ./results/rel_norm_merged_ASV_abundances_stool.qza"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Alpha diversity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved SampleData[AlphaDiversity] to: ./results/rarefied_asv_alpha_diversity.qza\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "#Alpha diversity for ASV\n",
    "!qiime diversity alpha \\\n",
    "  --i-table ./results/norm_merged_ASV_abundances.qza \\\n",
    "  --p-metric shannon \\\n",
    "  --o-alpha-diversity ./results/rarefied_asv_alpha_diversity.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved SampleData[AlphaDiversity] to: ./results/rarefied_asv_alpha_diversity_stool.qza\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "#Alpha diversity for ASV\n",
    "!qiime diversity alpha \\\n",
    "  --i-table ./results/norm_merged_ASV_abundances_stool.qza \\\n",
    "  --p-metric shannon \\\n",
    "  --o-alpha-diversity ./results/rarefied_asv_alpha_diversity_stool.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_diversity_artifact = Artifact.load('./results/rarefied_asv_alpha_diversity.qza')\n",
    "alpha_diversity_results = alpha_diversity_artifact.view(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_diversity_artifact_stool = Artifact.load('./results/rarefied_asv_alpha_diversity_stool.qza')\n",
    "alpha_diversity_results_stool = alpha_diversity_artifact_stool.view(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "meta_df = pd.read_csv('./results/meta_df.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Material</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>new_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <td>seren</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>BSPSPC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0480_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>BSPSPC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>BSPSPC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>BSPSPC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>stool</td>\n",
       "      <td>BSPSPC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>758 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Material   Group\n",
       "new_id                                \n",
       "2020-023_PSC_0001_srn    seren     PSC\n",
       "2020-023_PSC_0006_srn    seren     PSC\n",
       "2020-023_PSC_0007_srn    seren     PSC\n",
       "2020-023_PSC_0010_srn    seren     PSC\n",
       "2020-023_PSC_0015_srn    seren     PSC\n",
       "...                        ...     ...\n",
       "2020-023_SPC_0409_stl    stool  BSPSPC\n",
       "2020-023_SPC_0480_stl    stool  BSPSPC\n",
       "2020-023_SPC_0515_stl    stool  BSPSPC\n",
       "2020-023_SPC_0726_stl    stool  BSPSPC\n",
       "2020-023_SPC_0741_stl    stool  BSPSPC\n",
       "\n",
       "[758 rows x 2 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "meta_df['Combined'] = meta_df['Group'] + '_' + meta_df['Material']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data = pd.concat([alpha_diversity_results, meta_df['Combined']], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data = merged_data.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shannon_entropy</th>\n",
       "      <th>Combined</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_srn</th>\n",
       "      <td>5.770901</td>\n",
       "      <td>PSC_seren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_srn</th>\n",
       "      <td>5.995328</td>\n",
       "      <td>PSC_seren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0007_srn</th>\n",
       "      <td>6.006043</td>\n",
       "      <td>PSC_seren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0010_srn</th>\n",
       "      <td>5.317529</td>\n",
       "      <td>PSC_seren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0015_srn</th>\n",
       "      <td>5.887321</td>\n",
       "      <td>PSC_seren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0189_stl</th>\n",
       "      <td>5.982533</td>\n",
       "      <td>BSPSPC_stool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>5.852918</td>\n",
       "      <td>BSPSPC_stool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>6.651795</td>\n",
       "      <td>BSPSPC_stool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>5.988011</td>\n",
       "      <td>BSPSPC_stool</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>5.580220</td>\n",
       "      <td>BSPSPC_stool</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>721 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       shannon_entropy      Combined\n",
       "2020-023_PSC_0001_srn         5.770901     PSC_seren\n",
       "2020-023_PSC_0006_srn         5.995328     PSC_seren\n",
       "2020-023_PSC_0007_srn         6.006043     PSC_seren\n",
       "2020-023_PSC_0010_srn         5.317529     PSC_seren\n",
       "2020-023_PSC_0015_srn         5.887321     PSC_seren\n",
       "...                                ...           ...\n",
       "2020-023_SPC_0189_stl         5.982533  BSPSPC_stool\n",
       "2020-023_SPC_0409_stl         5.852918  BSPSPC_stool\n",
       "2020-023_SPC_0515_stl         6.651795  BSPSPC_stool\n",
       "2020-023_SPC_0726_stl         5.988011  BSPSPC_stool\n",
       "2020-023_SPC_0741_stl         5.580220  BSPSPC_stool\n",
       "\n",
       "[721 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_data_stool =  pd.concat([alpha_diversity_results_stool, meta_df['Group']], axis=1).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shannon_entropy</th>\n",
       "      <th>Group</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0001_stl</th>\n",
       "      <td>6.230038</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0002_stl</th>\n",
       "      <td>4.669107</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0003_stl</th>\n",
       "      <td>6.509281</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0005_stl</th>\n",
       "      <td>6.538380</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_PSC_0006_stl</th>\n",
       "      <td>6.888184</td>\n",
       "      <td>PSC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0189_stl</th>\n",
       "      <td>5.961575</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0409_stl</th>\n",
       "      <td>5.902540</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0515_stl</th>\n",
       "      <td>6.633840</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0726_stl</th>\n",
       "      <td>5.962374</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-023_SPC_0741_stl</th>\n",
       "      <td>5.580203</td>\n",
       "      <td>HC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>560 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       shannon_entropy Group\n",
       "2020-023_PSC_0001_stl         6.230038   PSC\n",
       "2020-023_PSC_0002_stl         4.669107   PSC\n",
       "2020-023_PSC_0003_stl         6.509281   PSC\n",
       "2020-023_PSC_0005_stl         6.538380   PSC\n",
       "2020-023_PSC_0006_stl         6.888184   PSC\n",
       "...                                ...   ...\n",
       "2020-023_SPC_0189_stl         5.961575    HC\n",
       "2020-023_SPC_0409_stl         5.902540    HC\n",
       "2020-023_SPC_0515_stl         6.633840    HC\n",
       "2020-023_SPC_0726_stl         5.962374    HC\n",
       "2020-023_SPC_0741_stl         5.580203    HC\n",
       "\n",
       "[560 rows x 2 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_data_stool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'merged_data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[17], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Define the groups\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m groups \u001b[38;5;241m=\u001b[39m [merged_data[merged_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCombined\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m group][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mshannon_entropy\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m group \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mPSC_seren\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mPSC_stool\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBSPSPC_seren\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBSPSPC_stool\u001b[39m\u001b[38;5;124m'\u001b[39m]]\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# Perform Kruskal-Wallis test\u001b[39;00m\n\u001b[1;32m      5\u001b[0m kruskal_stat, kruskal_pvalue \u001b[38;5;241m=\u001b[39m kruskal(\u001b[38;5;241m*\u001b[39mgroups)\n",
      "Cell \u001b[0;32mIn[17], line 2\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Define the groups\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m groups \u001b[38;5;241m=\u001b[39m [\u001b[43mmerged_data\u001b[49m[merged_data[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCombined\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m==\u001b[39m group][\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mshannon_entropy\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;28;01mfor\u001b[39;00m group \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mPSC_seren\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mPSC_stool\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBSPSPC_seren\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mBSPSPC_stool\u001b[39m\u001b[38;5;124m'\u001b[39m]]\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# Perform Kruskal-Wallis test\u001b[39;00m\n\u001b[1;32m      5\u001b[0m kruskal_stat, kruskal_pvalue \u001b[38;5;241m=\u001b[39m kruskal(\u001b[38;5;241m*\u001b[39mgroups)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'merged_data' is not defined"
     ]
    }
   ],
   "source": [
    "# Define the groups\n",
    "groups = [merged_data[merged_data['Combined'] == group]['shannon_entropy'] for group in ['PSC_seren', 'PSC_stool', 'BSPSPC_seren', 'BSPSPC_stool']]\n",
    "\n",
    "# Perform Kruskal-Wallis test\n",
    "kruskal_stat, kruskal_pvalue = kruskal(*groups)\n",
    "\n",
    "# If the Kruskal-Wallis test is significant, proceed with Dunn's test\n",
    "if kruskal_pvalue < 0.05:\n",
    "    # Perform Dunn's test for pairwise comparisons\n",
    "    results = pg.pairwise_ttests(data=merged_data, dv='shannon_entropy', between='Combined', padjust='bonferroni')\n",
    "\n",
    "    # Display the results\n",
    "    print(\"Dunn's Test Results:\")\n",
    "    print(results)\n",
    "else:\n",
    "    print(\"Kruskal-Wallis test not significant. No post-hoc test needed.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "results.to_csv('./results/alpha_pairwise_ttest_results.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kruskal-Wallis test not significant. No post-hoc test needed.\n"
     ]
    }
   ],
   "source": [
    "# Define the groups\n",
    "groups = [merged_data_stool[merged_data_stool['Group'] == group]['shannon_entropy'] for group in ['PSC', 'BSPSPC']]\n",
    "\n",
    "# Perform Kruskal-Wallis test\n",
    "kruskal_stat, kruskal_pvalue = kruskal(*groups)\n",
    "\n",
    "# If the Kruskal-Wallis test is significant, proceed with Dunn's test\n",
    "if kruskal_pvalue < 0.05:\n",
    "    # Perform Dunn's test for pairwise comparisons\n",
    "    results = pg.pairwise_ttests(data=merged_data_stool, dv='shannon_entropy', between='Group', padjust='bonferroni')\n",
    "\n",
    "    # Display the results\n",
    "    print(\"Dunn's Test Results:\")\n",
    "    print(results)\n",
    "else:\n",
    "    print(\"Kruskal-Wallis test not significant. No post-hoc test needed.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kruskal_pvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'merged_data' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[20], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Create boxplots\u001b[39;00m\n\u001b[1;32m      2\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m6\u001b[39m))\n\u001b[0;32m----> 3\u001b[0m sns\u001b[38;5;241m.\u001b[39mboxplot(x\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCombined\u001b[39m\u001b[38;5;124m'\u001b[39m, y\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mshannon_entropy\u001b[39m\u001b[38;5;124m'\u001b[39m, data\u001b[38;5;241m=\u001b[39m\u001b[43mmerged_data\u001b[49m)\n\u001b[1;32m      4\u001b[0m plt\u001b[38;5;241m.\u001b[39mylim(\u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;03m# Show the plot\u001b[39;00m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'merged_data' is not defined"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create boxplots\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.boxplot(x='Combined', y='shannon_entropy', data=merged_data)\n",
    "plt.ylim(0)\n",
    "# Show the plot\n",
    "plt.savefig('./results/alpha_diversity.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create boxplots\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.boxplot(x='Group', y='shannon_entropy', data=merged_data_stool)\n",
    "plt.text(0.5, merged_data_stool['shannon_entropy'].max(), 'p < 0.05', ha='center', va='top', color='red')\n",
    "plt.ylim(0)\n",
    "# Show the plot\n",
    "plt.savefig('./results/alpha_diversity_stool.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Beta-diversity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved DistanceMatrix to: ./results/rarefied_asv_beta_diversity.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "#Beta diversity for ASV\n",
    "!qiime diversity beta \\\n",
    "  --i-table ./results/norm_merged_ASV_abundances.qza \\\n",
    "  --p-metric braycurtis \\\n",
    "  --o-distance-matrix ./results/rarefied_asv_beta_diversity.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved PCoAResults to: ./results/rarefied_asv_pcoa_result.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime diversity pcoa \\\n",
    "  --i-distance-matrix ./results/rarefied_asv_beta_diversity.qza \\\n",
    "  --o-pcoa ./results/rarefied_asv_pcoa_result.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved DistanceMatrix to: ./results/rarefied_asv_beta_diversity_stool.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "#Beta diversity for ASV\n",
    "!qiime diversity beta \\\n",
    "  --i-table ./results/norm_merged_ASV_abundances_stool.qza \\\n",
    "  --p-metric braycurtis \\\n",
    "  --o-distance-matrix ./results/rarefied_asv_beta_diversity_stool.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mSaved PCoAResults to: ./results/rarefied_asv_pcoa_result_stool.qza\u001b[0m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!qiime diversity pcoa \\\n",
    "  --i-distance-matrix ./results/rarefied_asv_beta_diversity_stool.qza \\\n",
    "  --o-pcoa ./results/rarefied_asv_pcoa_result_stool.qza"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the PCoA results from the Qiime artifact\n",
    "pcoa_results = Artifact.load('./results/rarefied_asv_pcoa_result_stool.qza')\n",
    "\n",
    "# Convert the PCoA results to a pandas DataFrame\n",
    "pcoa = pcoa_results.view(OrdinationResults)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "pcoa_df = pcoa.samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def confidence_ellipse(x, y, ax, n_std=3.0, facecolor='none', **kwargs):\n",
    "    \"\"\"\n",
    "    Create a plot of the covariance confidence ellipse of *x* and *y*.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    x, y : array-like, shape (n, )\n",
    "        Input data.\n",
    "\n",
    "    ax : matplotlib.axes.Axes\n",
    "        The axes object to draw the ellipse into.\n",
    "\n",
    "    n_std : float\n",
    "        The number of standard deviations to determine the ellipse's radiuses.\n",
    "\n",
    "    **kwargs\n",
    "        Forwarded to `~matplotlib.patches.Ellipse`\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    matplotlib.patches.Ellipse\n",
    "    \"\"\"\n",
    "    if x.size != y.size:\n",
    "        raise ValueError(\"x and y must be the same size\")\n",
    "\n",
    "    cov = np.cov(x, y)\n",
    "    pearson = cov[0, 1]/np.sqrt(cov[0, 0] * cov[1, 1])\n",
    "    # Using a special case to obtain the eigenvalues of this\n",
    "    # two-dimensional dataset.\n",
    "    ell_radius_x = np.sqrt(1 + pearson)\n",
    "    ell_radius_y = np.sqrt(1 - pearson)\n",
    "    ellipse = Ellipse((0, 0), width=ell_radius_x * 2, height=ell_radius_y * 2,\n",
    "                      facecolor=facecolor, **kwargs)\n",
    "\n",
    "    # Calculating the standard deviation of x from\n",
    "    # the squareroot of the variance and multiplying\n",
    "    # with the given number of standard deviations.\n",
    "    scale_x = np.sqrt(cov[0, 0]) * n_std\n",
    "    mean_x = np.mean(x)\n",
    "\n",
    "    # calculating the standard deviation of y ...\n",
    "    scale_y = np.sqrt(cov[1, 1]) * n_std\n",
    "    mean_y = np.mean(y)\n",
    "\n",
    "    transf = transforms.Affine2D() \\\n",
    "        .rotate_deg(45) \\\n",
    "        .scale(scale_x, scale_y) \\\n",
    "        .translate(mean_x, mean_y)\n",
    "\n",
    "    ellipse.set_transform(transf + ax.transData)\n",
    "    return ax.add_patch(ellipse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the covariance matrix\n",
    "cov_matrix = np.cov(pcoa_df.T)\n",
    "\n",
    "# Calculate the eigenvalues of the covariance matrix\n",
    "eigenvalues = np.linalg.eigvalsh(cov_matrix)\n",
    "\n",
    "# Calculate the total variance\n",
    "total_variance = sum(eigenvalues)\n",
    "\n",
    "# Calculate the percentage of variance explained by each principal component\n",
    "explained_variance_ratio = (eigenvalues / total_variance) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "first_cmp = explained_variance_ratio[-1]\n",
    "second_scmp = explained_variance_ratio[-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAINCAYAAAA3GxeQAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy89olMNAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9eXylZX3/jz/v7ewnJ8lkmclMJrMvDKsDDEsV0DKU2ioulYKgVtHyo4uU9mNFqlVbwVo/SG3rgstHUEH0K2JVFMYFpYAgIwMMM8PsycwkmWSynf2ce/v9ceecOUlOknOSsybX8/HgMeSs17mv676u1/W+3otk27aNQCAQCAQCgUCwCJCr3QCBQCAQCAQCgaBSCPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0qNVuQK1jWRa9vb0Eg0EkSap2cwQCgUAgEAgEk7Btm0gkQkdHB7I8s21XiN9Z6O3tpbOzs9rNEAgEAoFAIBDMwrFjx1ixYsWMrxHidxaCwSDgXMyGhoaC3qPrOo8//jjbt29H07RyNk8wC6IvagfRF7WF6I/aQfRF7SD6onYoti/C4TCdnZ1Z3TYTQvzOQsbVoaGhoSjx6/P5aGhoEDdPlRF9UTuIvqgtRH/UDqIvagfRF7XDXPuiEBdVEfAmEAgEAoFAIFg0CPErEAgEAoFAIFg0CPErEAgEAoFAIFg0CJ/fEmDbNoZhYJom4PipqKpKMpnMPiYARVFQVVWkjBMIBAKBQFA1hPidJ+l0mr6+PuLxePYx27ZZunQpx44dE0JvEj6fj2XLluFyuardFIFAIBAIBIsQIX7ngWVZHDlyBEVR6OjowOVyIUkSlmURjUYJBAKzJlpeLNi2TTqdZnBwkCNHjrB+/XpxbQQCgUAgEFQcIX7nQTqdxrIsOjs78fl82cctyyKdTuPxeITAy8Hr9aJpGt3d3dnrIxAIBAKBQFBJhDIrAULgFo64VgKBQCAQCKqJUCICgUAgEAgEgkWDEL8CgUAgEAgEgkWDEL8CgUAgEAgEgkWDEL+LlPe85z1IkoQkSWiaxpo1a/iHf/gHYrEYAN///vfZtm0boVCIYDDIli1b+Pu///sJn5FOp/nMZz7DOeecg8/no6WlhUsvvZT/9//+H7quV+NnCQQCgUAgEMyIyPZQA1iWzf6BCGNxnZBPY0NbEFkuf37gP/qjP8oK1SeffJKbbrqJWCzG2972Nv78z/+cO++8kze96U1IksSePXv4xS9+kX1vOp3mqquu4sUXX+Rf/uVfuPTSS2loaOC3v/0tn/3sZznvvPM499xzy/4bBAKBQCAQCIpBiN8qs7N7mPue7ubgQJS0YeJSFda1BXj3JV1s7Wou63e73W6WLl0KwPXXX8+vfvUrHnnkEdxuN3/wB3/A//k//yf72g0bNnDNNddk/77nnnv4zW9+w/PPP895552XfXzNmjX82Z/9Gel0uqxtFwgEAkH5qZZxRiAoJ0L8VpGd3cN86id7GY3rtAXdeDQ3Sd3kld4xPvWTvdzxxs1lF8C5eL1edF1n6dKlPPDAA+zevZszzzwz72u//e1v84d/+IcThG8GTdPQNK3czRUIBDWMEE31TzWNMwJBORHit0pYls19T3czGtdZtcSXLYPsd6v4XArdw3Huf7qb8zqbKrJgPPfcczzwwAO84Q1v4G/+5m948sknOeuss+jq6uKiiy5i+/btvPOd78TtdgNw4MABLr/88rK3SyAQ1B9CNNU/tWacEQhKiQh4qxL7ByIcHIjSFnRnhW8GSZJoDbg5MBBl/0CkbG348Y9/TCAQwOPxcPHFF/O6172O//zP/8Tv9/OTn/yEgwcP8k//9E8EAgH+/u//ngsvvJB4PA445Yont1sgEAgyomn3iTEaPCormnw0eNSsaNrZPVztJgpmYbJxxu9WUWQJv1ulq9nHWELn/qe7sSy72k0VCOaEEL9VYiyukzZMPJqS93mPppA2TMbi5cuacMUVV7Br1y5effVVkskkDz/8MG1tbdnn165dy0033cRXv/pVfv/737Nnzx4eeughwPEB3rt3b9naJhAI6g8hmhYGtWCcEQjKiRC/VSLk03CpCkndzPt8UneOCkO+8vnO+v1+1q1bR1dX16w+uqtWrcLn82VToV1//fX8/Oc/54UXXpjyWsMwsq8TCASLByGaFga1YJwRCMqJEL9VYkNbkHVtAQajKWx7ohXEtm0GoynWtwXY0BaseNs+/vGP86EPfYgnnniCI0eO8MILL/De974XXde58sorAbj11lu59NJLecMb3sB///d/8+KLL3L48GG++93vsm3bNg4cOFDxdgsEguoiRNPCoBaMMwJBORHit0rIssS7L+ki5NXoHo4TSxmYlk0sZdA9HCfk1XjXJV1ViY6+7LLLOHz4MO9617vYtGkTV199Nf39/Tz++ONs3LgRcNKk7dixgw996EN8+ctf5qKLLuKCCy7g85//PH/7t387bZYIgUCwcBGiaWFQy8YZgaAUiGwPVWRrVzN3vHFzNir6VDSFS1U4syPEu8ocFf2Nb3xj2ueuuOIKrrjiilk/w+128+EPf5gPf/jDJWyZQCCoVzKi6ZXeMXwuZYLrQ0Y0ndkREqKpxskYZz71k710D8dpDbjxaM6mZjCaqqpxRiAoBUL8VpmtXc2c19kk8mEKBIK6R4imhUM1jTMCQbkR4rcGkGWJTUsbqt0MgUAgmDdCNC0chHFGsFAR4lcgEAgEJUWIpoWDMM4IFiJC/AoEAoGg5AjRJKg3LMtm/0knDd/+kxE2d1Smwqqg8gjxKxAIBAKBYFGTKcndPRjhvV3wkYd309UaFCW5Fygi1ZlAIBAIBIJFS25J7qDHyVEd9CiiJPcCRohfgUAgEAgEi5IpJbldzoG43yVKci9khPgVCAQCgUCwKBEluRcnQvwKBAKBQCBYlIiS3IsTIX4XKe95z3u45pprpjz+xBNPIEkSo6OjgFOV6d5772Xbtm0EAgEaGxs5//zzueeee4jH45VttEAgEAgEJUSU5F6cCPErmJEbb7yRW2+9lTe/+c386le/YteuXXz0ox/lhz/8IY8//ni1mycQCAQCwZzJlOQejKaw7Yl+vZmS3OvbAqIk9wJDpDqrBSwLBvdCYhS8jdC6GeTq70u++93v8u1vf5tHHnmEN7/5zdnHV61axZve9CbC4XAVWycQCAQCwfyYXJJ7WdCx8MbSBn0RXZTkXqAI8Vttep6F5+6FU6+CkQLVDS0b4cIPwMptVW3at7/9bTZu3DhB+GaQJIlQKFSFVgkE48noRfUwgUBQAnJLcncPOoFtkaQpSnIvYIT4rSY9z8LjdzgW32A7qF4wEtD3kvP49k+VVQD/+Mc/JhAITHjMNE/7PR04cICNGzeW7fsFgrmQSUZ/cCBK2nD88da1BUQyeoFAMGcyJbn39o5wcOeT3PnWM0WFtwVM9c/WFyuW5Vh8E6PQvAZcAZAV59/m1ZAYg999xXldmbjiiivYtWvXhP+++tWvZp+3bXtK6heBoJrkJqNv8KisaPLR4FFFMnqBQDBvZFliQ7vj27uhXZwmLWSE5bdaDO51XB2C7TBZYEoSBNtgcJ/zuvYtZWmC3+9n3bp1Ex47fvx49v83bNjA3r17y/LdAkGxTE5Gn9mY+d0qPpdC93Cc+5/u5rxOYa0RCAQCwfQIy2+1SIyO+/h68z+vep3nE6OVbNUErr/+evbv388Pf/jDKc/Zts3Y2FgVWiVYrIhk9AKBQFAZLMtmX3+YZw8Psa8/vOAq3AnLb7XwNjrBbUbCcXWYjJFwnvc2VrplWd7xjnfwgx/8gOuuu46PfvSjXHnllbS2tvLyyy/zuc99jr/5m7/JmytYICgHp5PRu/M+79EUTkVTIhm9QCAQzIPFEFchLL/VonWzk9UhMgCTcgti287jrZuc11UJSZJ44IEHuPvuu/nBD37AZZddxtlnn83HP/5x3vzmN3PVVVdVrW2CxYdIRi9YiFiWzf6TzmnF/pORBWdhE9QXiyWuQlh+q4UsO+nMHr8Dho84Pr6ZbA+RAcfie8H7y5bv9xvf+Ebexy+//PIJib5lWebmm2/m5ptvLks7BIJCySSjf6V3DJ9LmeD6kElGf2ZHSCSjF9QNGQtb92CE93bBRx7eTVdrcEFZ2AT1w2KKqxCW32qycpuTzmzZ2ZAcg9Fu59+Oc2D7v1Y9z69AUEtkktGHvBrdw3FiKQPTsomlDLqH4yIZvaCuyLWwBT0KAEGPsuAsbIL6YTHFVQjLb7VZuQ1WXFCTFd4EglojNxn9wYEop6IpXKoiktEL6orJFjZNck7b/C6VrmZtQVnYBPXDYoqrEOK3FpDlsqUzEwgWGplk9KLCm6BemWphy/HzlST8LpUXj4/y2J5+rjpjqRjbgoqQG1fhd0+VhwsprkKIX4FAUHfIssSmpQ1zeq8ojVw5xLXOz3QWtrGkzpHhJNGkQdq0+PSj+/jpy/3CB1hQERZTXIUQvwKBYNGwGFL41AriWk/PdBa2QwNRYjoosoRLlQl5T0fZ3/HGzYv+ugnKSyau4lM/2Uv3cJzWgBuP5ozTwWhqQcVVCMfSEmBPTlUmmBZxrQTVYrGk8KkFxLWemYyFbTCawrbtrNODYdp4NBnTtgm4VVoCbrqafYwldO5/ulukQROUnUxcxZaOEOGkwfGROOGkwZkdoQW1AROW33mgaY7fSzwex+udplKbYALxeBw4fe0EgkqwmFL4VBtxrWdnsoWt0S1Dk2PxjRsWqiyxovH0tcuNsp+ru49AUCiLIa5CiN95oCgKjY2NDAwMAODzOZOVZVmk02mSySSyyNoAOBbfeDzOwMAAjY2NKIpS7SYtaISv5USKSeEjxMX8ENe6MHIzl+zrHQHAwibo0VjR6KMxJ6hoIUXZC+qD+cRV1ANC/M6TpUuXAmQFMDhCL5FI4PV6p0z+i53GxsbsNRPMzHQCdjZhuxB9Lecr5kdiaSJJHZciYdvgd08M5hDionQspnRJ8yVjYfvZ7hPoR3ayeomfkN8zZd1YSFH2lUYYAgT5EOJ3nkiSxLJly2hra0PXnclc13V+85vf8LrXvU4c7+egaZqw+BbIdAJ225pmnj08PK2wzfhajsZ12oJuPJqbpG7WddDMfMX8zu5hvvzrwwxEUgxGU6iyk0pqRdNp65oQF6VjMaVLKgWyLPGGjW387AjE0yYh/8TnF1qUfSVZiIYAQWkQ4rdEKIqSFXaKomAYBh6PR4hfQdFMJ2B3dg/z870nafJpdDb5pgjb26/ezDd/W/u+lvtPRoim7YKsMPMV87nvD7gV4mkTVZaJpAwODERY3xYk5FWFuCghiyldUqnI3AMNXnXBR9lXioVoCBCUDiF+BYIaYrpgIZ9LwTBtdNNCNy18bhWJicL2C08cpH8sWbO+lruOOX6NH3l4NzHdmtUKM9/AqcnvH0u6OHAyQtq00GSJtGlzdChGyKvS6HMJcVEiFlO6pFLzD1dt5JvPnhDVC+eJCLoUzIYQvwJBDTFdsFAsZRJLG3hUhXjaIpYyCIwfKWeE7ZFTMUzLpr3Bk/ezq+lrubN7mM8+9irXd0DQo9AU8MxqhZlv4NTk9zd6Nda3Bzk+EieWMrGxiaYMzl4e4q/fsE6IixIiylDPjXM7m9i6qlX4qM4TEXQpmA0hfgWCGmK6YCHdsrBs8KgSScOx/ubi0RRMy0aWpJrztcxYYcYSBgB+l4qBNKsVZr6BU/ne3+jVCHlDxFIGKd1kKJbmLy9bK8RYGVgM6ZLKwUKPsq8EIuhSMBt1l4frC1/4AqtXr8bj8bB161aefPLJaV/78MMPc+WVV9La2kpDQwMXX3wxjz32WAVbKxAUR26wUC6aLCNLoJuOwNWUibduUjcJejRWt/izifNzyfharm8LVMTX0rJs9vWHefbwEI/t6efAyQgtAdeU1022wuQy3bXIMJuYn+79EhBwq3g0haBHo9Ev/PLLRUbIbVuzhE1LG4TwFVSE+c4dgoVPXYnfhx56iFtvvZU77riDF154gde+9rVcffXV9PT05H39b37zG6688koeffRRdu7cyRVXXMGf/umf8sILL1S45QJBYUyu/JTB71bwu1SShonPJU+w7OYK2796/VpCXo3u4TixlIFp2cRSBt3D8Yr5Wu7sHubWh3Zx20MvcscPXubffrqPYyNx0oaV9/UeTSFtmFOsMNNdCyhMzM/3/QKBoD4R975gNupK/N599928733v46abbmLz5s3cc889dHZ28sUvfjHv6++55x4+9KEPccEFF7B+/XruvPNO1q9fz49+9KMKt1wgKIxMsNBkARtPm6iKY/HVFJn4NML2glVLqlqaMn9ZW420YXNoMJr3PdNZYaa7FoWK+fm+XyAQ1Cfi3hfMRt34/KbTaXbu3MmHP/zhCY9v376dp59+uqDPsCyLSCRCc/P0AiCVSpFKpbJ/h8NhwMndm8njOxu5+X4F1aUe++LsjiC3/9F6Hnj2GIcHY4zFkrhUhW1djWxd1cTzR0cmPH5OR5DrtnVydkcQXdc5uyPIv791CwcHo4QTOg1ejXWtAWRZKut1sCybbz19hHgyzbolmQIvNkuDGsNRhUQyDYBim47vAY4VZiyWZPOyBlY3eaa0b7prMfk3T8d837+Qqcd7Y6Ei+qL0zPXeF31ROxTbF8X0mWRPPhOoUXp7e1m+fDlPPfUUl1xySfbxO++8k/vuu49XX3111s/493//dz796U+zd+9e2tra8r7m4x//OJ/4xCemPP7AAw/g8/nm/gMEAoFAIBAIBGUhHo9z/fXXMzY2RkPDzEGjdWP5zTA5bYlt2wWVEH7wwQf5+Mc/zg9/+MNphS/A7bffzm233Zb9OxwO09nZyfbt22e9mBl0XWfHjh1ceeWVoshFlRF9UTmePzrMJ3+0h+VNXpQ892QkkeLajhG+fCiAjYxLVVjb6ue6bZ2c29lUhRZXHsuy81rkq4G4N2oH0Re1g+iL2qHYvsic1BdC3YjflpYWFEWhv79/wuMDAwO0t7fP+N6HHnqI973vfXzve9/jD//wD2d8rdvtxu2emh5F07Sib4S5vEdQHkRflJ+moBdJUYmmbfzuqWWs5fEKiH/9hxtZEvAuutRXtVpqVdwbtcNi6gvLsms6Dd5i6otap9C+KKa/6kb8ulwutm7dyo4dO3jLW96SfXzHjh28+c1vnvZ9Dz74IO9973t58MEHeeMb31iJpgoEi5LZytoORdPQDm/Y2IbbPTXt2UJGlFoVCE5TqxvBWqHWNwYLgboRvwC33XYbN954I+effz4XX3wx9957Lz09Pdx8882A47Jw4sQJ7r//fsARvu9617v4j//4Dy666KKs1djr9RIKhar2OwSChchsZW1bfGr2dYuJfKVWbdvGtqHBozIQSXHfU0dFqdUFTiGCJpMfeyGLHrERnBmxMagMdSV+r732WoaGhvjkJz9JX18fZ555Jo8++ihdXV0A9PX1Tcj5++UvfxnDMPirv/or/uqv/ir7+Lvf/W6+8Y1vVLr5AsGCZ6aytjdsW07vy89Uu4kVZ3Kp1dG47pRYThtYNmDDE/sHeWTXCd76mhXVbq6gDBQqaD788Mu8OhAvWPTUm4Uw30YQmLXaY61RrusuNgaVo67EL8Att9zCLbfckve5yYL2iSeeKH+DBALBBKYra2uaBr0vV7t1lSe31OpoXOfAQATDsnEpMooEpg2xtMEXnzhE1xIfW7ua607UCKanEEFjmU7p7719YRr9noJETz1aCCdvBHOZXO2xVks8l+u6L5SNQb1Qd+JXIBDUPpmytrmY+SuNLngypVYTaafoiGHZeFX59OJvO0I4qZvc/3Q3lm3zzWd66krUCPJTiKC576mjyFhc4YeVTV5MSZnymsmip14thLkbwXx4NIVT0dSUao9zpdSbyHJe94WwMagnhPgVCASCMpIJBPx9zwixtIFLOS18bSBtWgQ9Kh2NXl48Psr+RyKkDKuuRI0gP4UImt29YVyyzRVrp6byzCd66tlCmNkIJnVzQon2DNNVe5wLpbbQlvu6V3pjsNipq/LGAoFAUG9kAgG9mkLKsJxgN8CwbBK6iSpLrGjyjS9uaUYTzuLqd6sosoTfrdLV7GMsoTuWYasu6hIJyBU0U1P/gSNoUrpJypj+WMSjKaQNMyt6irEQ1hqZjeBgNMXk+lq2bTMYTbG+LcCGtuC8vid/mXU1u4nc2T1c9GeW+7rnbgzyUcqNgUCIX4FAICg7W7ua+f9dvgavpqCbjug1LJugR2V9e5BGr8ZILI1uWrQGXHUnagT5KUTQuDUFt5pfHGdekyt6ChHUuWK5lshsBENeje7hOLGUgWnZxFIG3cNxQl6Nd13SNS+L9WQLbak2keW+7pXaGAgchPgVCASCCnDNuSu4bEMrSwIuNrYH2NLRwJaOEI1eDdu2ORVNoSkSTb78OZBrWdQI8lOIoDmzo4FNS4PZx/K9Jlf01LuFMJMRZktHiHDS8YMPJw3O7AiVxK2nXBbacl/3SmwMBKcRPr8CgUBQAWRZ4l2XdHHwkSgnwylaAi48qkzKsBiMpmjwOtPxYCRF0KPhd08sFFLrokYwldlyX4e8Gu++dBWWadD78gmOjSQI+T1TXpMremYrJuMI6lBNWwinywhTCmFXat/ZTNDcSCxNW9DNseF42a77TKki3yUCXkuKEL8CgaAqLLZ0Xju7h/nmMz0kdJNw0mAolkZTJFoCbjqbfFi2Te9oksFoCrcq43c5voqNPq1uRI1gKoUIGl3X6X0ZNi1r4NWB+IyipxBBXQ8WwnwZYUpBKYPqJgfNGZbNWEInaZh0jvvpl/q6l3NjIDiNEL8CQQ1QD0KwlG2sxxyl8yE3RdLSBg9dS/yMxNKciqawgf5wEtOy6Wz20TMUQ7dsxpI6iYEInU1ekoZVN6JGMJVCBc2n33oWR0aSs95jwkI4PaWyjO86NsJdPzswJa2ZblrE0yb94SSqLJXlupdrYyA4jRC/AkGVqQchWMo2TreoLNR0XtOlSGoNulkScPG7oyPY2FzY1YQsy3g0heMjcaJJg4RucmwkweUbWnn3pasW1HVZbBQiaIoRPcJCmJ9SWcYfePZY3rRmG9uDHB2K0dXs5y8vW0ujf+Fe93owyswVIX4FgipSD8nqS93G6RaVWshRWo7JfqYAnHjazEadx9MWAY9Mo1cj5A0RSxlEkjpJw+Lmy9dyRkdoXu0QLDyEhTA/pbCMHx6MTRs01xb0cDKSotGvLdjrXw9GmfkgxK9AkEMld7r1kKy+HG2caVGpZhWjck32MwXg6KaFjY2EhG5Z2cclIOBW8Y5bgSNJY87fLxAsRuZrGU8bJk0BT97nFnrBiXowyswXIX4Fi5J8IveFYyMV3enWQznLcrSxFheVck72MwXgaIqMhHNdNXlq5kmR4aH0LOSjXMFE5mMZr1QlulqjHowypUCIX8GiI5+Fr9mvMRBJYZh2xXa69VDOshxtrLVFpdyT/UwBOD6XMv6ZNj7XRPErMjyUnoV+lCsoHWta/bzUG6nbdHJzpR6MMqVAFLkQLCrylb0MelR2HRujeyhOk0+rWFnZaiSrtyybff1hnj08xL7+8Ky/KdPG4ViakXiaaMog9x1zaeOaVn9NVTEqd9nSmZLX9wzH6Wj00NHopWckIRLbl5FylLwVLFyu39a5YAtOzLQO1HMFwWIQll/BomE6Cx84wkuS4PhogpBXyz5Xzp1upZPVz8XqFUnqjCXSDEbSKDIosozfrbCiyUfIo86pjddv66T7ZwdqJkdpJSzwswXgAIsvbZVlweBeSIyCtxFaN0Me14/SfNXiOMqtBIvFbeTczqaSpJOrtes12zpQyjzJtYwQv4JFw3QWPifoCDyqQixlEEuZBDynb41yuR9UMln9XHxad3YPc9ej+7BtcKkSpuUEYoUTOvuSYRp9Gu0NnqLbWKpFpVRUarKfLQBnUaWt6nkWnrsXTr0KRgpUN7RshAs/ACu3lfzrFstRbrlZbG4j8w2aq7XrVcg6cF5nU91XECwEIX4Fi4bpLHyaIiNLErZtY9lMiLqH8u50K5Gsfi5Wr9z3bFoaZCxhcHwkTixtIEkSuulco9uvnpsvdC3lKK2kBX6mAJxypK2qNasT4Ajfx+9wLL7BdlC9YCSg7yXn8e2fKrkArgf/+umolT5cDBkA8jHX+7LWrlfB68C1TQuiguBsCPErWDRMZ+Hzu1X8boWxhI4qSxOi7iux0y23EJyL1Wvyexp9GiFvA7GUiW5ZGKaFbtoEvXOfQmolR+lCKRc7mVqzOgGOq8Nz9zrCt3kNZMajKwDNfhg+Ar/7Cqy4oKQuEPV6lFsrfSjcRoqjFq9XMevAYqggKMSvYNEwnYVPApY3ehnNWn1sTMuuqPgppxCci9Ur33skScq6g5iWzfGReE1ayubCQpvsC7E6nd1RhWPLwb2Oq0Ow/bTwzSBJEGyDwX3O69q3lOxrK+1fXwpqyXIo3EaKoxavV7HrQC2dzpUDIX4FiwZZlrjxoi4+9sPd7OuP0BJw0+R3kdJNxhI6XUt8tAU9DMfSDMXSdS1+cpmL1ateLWXzYaFM9oVanT7z1tKJy4JJjI77+HrzP696wRhwXldC6s26X2uWw3p2G6kGY3GdlGFiWgoj8TSaIuN3q2R6qhrXay5zeq2czpUDIX4Fi4ad3cN887fdJHSTcFJnKOZMSi0BF+esaORdl3QtCPEzmblYverRUpaPYv0lF8JkX6jV6eBgtPKN8zY6wW1GwnF1mIyRcJ73Npb8q+vJuj9bH7YE3LzcO8b3f3+cs1aEyj5PLcbN8Hw4MRpnMJKibzQJEsiSlM2S0+jVqnK9FsqcXiqE+BUsCnYdG+Gunx1gNK6ztMFDV7OPkXiaU9E0Xk3hhotXZhe/ehc/k5mL1aveLGX5qBV/yUpTqJUunKiCla51s5PVoe8lx8c3V9jZNkQGoOMc53VloF6s+zP14WhC59hwjNG4wT079hPyuco+roVwKpyd3cN885luTMvGwsanKlg2RJIGB05GWNcWYCyhl+V6zbTZXwhzeikRRS4Ei4IHnj2WPUL0u1VURaY16GHT0iBp0+Jbz/SUvIhFLZGxem3pCBFOOpkbwkmDMztC0/oOzuU9tcJiLmhQaPGUBm8VrHSy7KQz84ac4LZ0FCzT+Xf4iGPxveD9cw52y5e8f/Jj4Gxwt61ZwqalDTW52E/Xh6MJnQMnI4QTBqossazRW5FxPVOhloVQ9KFUZNxVxhIGm5YGcSkyScPJjONRZdKmxf6TURrKcL12dg9z60O7uO2hF7njBy9z20MvcutDuyaMiXqe00uNsPwKFgWHB2M1FXxQDeZi9aoXS1kuteYvWWkKtdKtaw1wsBoNXLnNSWeWzfM74Lg6dJzjCN85pjmbrmw5SAzH0nVl/c/XhzZwfCSObljIskTQo9LgUZEkqSLjup7cRqpFrruK362yvi2YTRFp2SAjIUtw40WlvV7FBEfW45xeDoT4FSwK0oZJU8CT97nFFKwxF5/WevODrcVI60pSF8ebK7c56cxKVOEt3+I/GE3xu6MjAKxr9bOiyVc3eWnz9aFp2UQSBrYEmiyxovH0xq5S43ohC6eMy8BIJJH9u1gmu6tMThEpSxIjsRTLG6cJ+Jxju4vd7NfbnF4OhPgVLApqKVijXEnrayUZfrVZLJHpM/V3IVY6Xa/y75flkqQzy7f428CpaAoZkGSJU7E07Q2eurL+T+7DsUQaw7Jo9LnobPLROGm+qtS4XojCKffUwDYNbl4LH374ZW64ZHVRG6R8gYG5KSJjKQO3ppZ0ranGZn8hrDVC/AqKZrqBX8s3RGvQxZ7+GCuavATcanaSqHSwRrmCsBZrcFc+FkNkeiH9XQ9WulLMGfkW/0yZcremTPg7MO4mUC/W/9w+fPn4GF984hCtARcBz9SxuxDGdTWYfGoQcGlAmH194aJPCKoRGFjpzf5CWWuE+BUUxXQDf9uaZp49PFxzN8SuY86xZ89wnOFYmlPRFEGPxspmH25VrugxcLmS1tdSMvxaoJYi08uxISymv2vZSleqRTTf4q+bFpZto8gy2DbpSWXL68n6n+nDDW1Bnjxwild6x5ycsUWM61o2TFSTfKcGCs44afJrHB1O8l+/PMhXbjwfVZ3dJacaLkeV3OwvpLVGiF9BwUw38Hd2D/PzvSdp8ml0Nvlq5obY2T3MZx97les7cAIQvG56hmJEkgZ7+sIsC3my+X3L3b5yBWEt9uCufNSKz2s5LCQLpb9LuYjmW/w1RUaWJMxxv01ZYkLZ8nq0ks51XC8US105yHdqMJZ0NkSv9keJGTZPHxripvuf52/esK6g61XpwMBKbfYXytyTQaQ6ExTE5IHvd6soshNlbJg2ummhmxa+8cf9bpWuZh9jCZ37n+6ueBqx3JQzAH6XSrPPxTmdTZzbGWKJ38XqFj//98/OKWoyypdKqRCK8csqhnJ9br1T7ZQ+5Uq1thD6e7q5ZK5zRmbxH4ymsG3nPX63it+tkDJM0qaV/RtOC4L1bYGq5KWd6xwCxY/rxZzyrxBOnxo4Y2M0oXNowCn+osoSPk1BkmD/yUhR12trVzP3XHsud197Dp96y1ncfe05fO7ac8sy71QqDd1CmHtyEZZfQUFMN/BjKZNY2sCjKsTTFrGUQSDH0b9avnWZ9rYEXBMel2Dc7UHiZDjFwVPRgts1HwtKufyyFktw11yols9rOS0kC6G/Sx2gM51FtCXgZjSug23T4ndh2ZBMG1XNeDHdHHLjtuUFf0ah43qhWerKQe6pgc+tcnwkjmE6mxFFlkgZjghe0eRlKJYu6npV0uWoEtbmhTD35CLEr6Agphv4umVh2eBRJZKGY/3NpVo3xOn25j/WLLZd8z2mLZdfVrGfWw7fv1r2J6yGz2s5o68XQjBfORbR6Rb/C1c3YdtOnt/jI/Gq5qWdaQ757GNRru8o/LMKGdeLPeVfIeS6DCyxbWIpE/+4b69t26RNm6BHJeBWkSWppq9XuTf7C2HuyUWIX0FBTDfwNVlGlkA3bWRJQlMmetJU64YotMpVIe0qhQWlXH5ZxXxuOXz/hD/hVMppIalWMF8pNzjlWkSnW/yBqm/OZptD+kZi2deVioVmqSsHuacGx0cSGJaFJDlrWNKwUGU5m0+5Hq5XOTf7tRRIXAqEz6+gIPL51QH43Qp+l0rSMPG55AmLWTV96zLtHYqmpzxXbLtK4etULr+sQj/3hWMjJff9E/6E+Snlxmsy1SgzW0jZ1GKYbi6B+c8ZmcU/t3RxvsdmYj4+udMx2xyyZNw96+BgdN7flaGc43AhkTk12NAexLYhMX69Ah6nQlsmn/Jiv14LrcS1EL+Cgphu4MfTJqriWHw1RSZeIzdEpr0N3vHk4um5t2tyUMRkPJpC2jBntQiUKwhrts89r7OppAFGUPqgpYVEOcUdVDaYrxwbnFpeREst9DMUMocAhBOlsyqWexwuJLZ2NfPVd53PxWuW0ORzNiKb208LX3G9HKodSFxKhNuDoGCm86s7v6uZC3Py/NZKzfetXc38w1Ub6X35GSJJk5iuz6ldpTymLZdf1kyfu68/XHLfP+FPOD35ArDcmsLIeJ5pt6bwmq5G9g9E5tz3lQjmK2fAVKXTQRVCOXOYFjKHADR4S2dVrJWUf/WCqsr8zRvW8ZlHXwFixHUTVZXF9ZpEPRTPKQQhfgVFMdPAv+6ClTV3Q5zb2UTvy3DnW88kmrbn1K5S+zqVyy9rus8th++f8CecmVxx99LxUU5F06QME8t2cs7++2Ov0hJwc/aKxjn7R5c7mK/cG5xaWkTLnRlhtjlkKJqGdljXGijZb4La3GTUMsUYTGo50Lfc1HLxnEIR4ldQNNMN/Fq+ITa0B9GmyfwwG/VuQSlHgNFCi/wtB1u7mrFsm489EsGjyZimhY2NpioYls2paIqd3cMcH4nX5JFhJTY4tTJnlFvozzaHtPjU7OtKTS1tMuqBQgwmItC3/hE+vwJBAdSzr1M5fP+EP+HsWJbNN5/pIWVYyJIjovweDbcq49NkLBsM02Y0nq5J/+jFFDBVKr/+mZhpDvmHqzbO+XMLodigv1JTjiDCcrOhPZj3eolA34WBsPwKBAVSrxaUcliu690aXgky1sSAW2UgksKlymSuhiRJuBSZWNqgvaE2/aMXWmqjmajUScZ0c4hpGvS+PK+PrlkWkpVUFA5ZOAjLr0BQBNW2oMyVcliu69kaXgky1kRZBsu2USaNFUVi3AdYmrdVsRzUclaGUlPJk4x6nUPmQk1aSS0LTr4CR59y/rWs2d8zzkIr8buYEZZfgWCRUA7Ldb1awytBxppoWY7ANS0bNee6mOPBb5Zt16z7wGIJmBInGaWnJq2kPc/Cc/fCqVfBSIHqhpaNcOEHYOW2Wd8uAn0XDkL8CgQVohaig8sRYFQrQUu1RtZt4MQYPpdMNGWiyAoSmdKpFkG3SjRlcNbyxpp1H6jHDc5c7rXFIvQrRc2lQ+x5Fh6/AxKjEGwH1QtGAvpech7f/qlZBXA9BPrWwjpTC22YDSF+BYIKsJD83gSFkWtNTBomEibxtIEqyxiWjSKDqkg0+lw1b1Wspw3OfO61ehT6tUpNWUkty7H4JkaheQ1kxLgrAM1+GD4Cv/sKrLhgxo+pdT/4WlhnaqENhSB8fgWCMlOTfm+CipCxJm7taqY16EaRZdKmhSJDS8DN+TnPC+ZPKe61xeSTW05qKlvI4F7H1SHYflr4ZpAkCLbB4D7ndTNQy37wtbDO1EIbCkVYfgWCMlKTfm+CipJrTRyOpNnTH0aWYFmjlys3taOqwgaRYT7HpeW416p5fFsPR8czkc9Kats2sZRJ2jQZjKZ5TWeF3H0So+M+vt78z6teMAac183CdO4xW5Y1cPmmVgzTSetW6bFS7XWmFtpQDEL8CgRlpOb83gRVQZYlYimD7zx/bMJx4E9f7q+548BqMd/j0lLfa9U8vq2Xo+OZmBxE6FFlBqNpokkD3bJQZYnheJoXjo2U/zd5G53gNiPhuDpMxkhgK26OxlT6jzrWyZlyEU92jzkxmuBX+wb46pNHq9JftbDO1EIbikGYHASCMlJo8vyRWLruksAvKOaR/qgQJh8HLm/0osrw/NFh/ukHu/nd0aGSfl+9UYrj0lIWqqjm8W09HR3PRsZKuizk5fCpOCPxNABNPo01rQH6xpKV+U2tm52sDpEBmJTKDtsmMdLHzngbf70jySd/tAeADz/88oztyrjHqIrEt37bzSu94ar1VyWKtNRDG4pBWH4FgjJSSHSwYdl8+deHGYik6tbKU9fMM/3RbEw+DhxLGBw5FSGWNrBsOBVNcet3dnHPtedxwera7e9yHMNbls2+k2Hufnw/AxEnl648x+PSUkXiV/P4tt6Ojqcjd6wEvSpNPo0lARetARcuVcHvVrNZTyrym2TZuZ8fv8MJbgu2ZbM9JEb66I5p3KddSTDgIuCSgDD7+sJ86id7Z/TJr5X+qoUsFLXQhmIQ4lcgKCOzRQcfG4kTT5v0DMdpC7rxaG6Supm1GohgqDIznv7ITowSd7eQdjfjstP4+l5EKjD90WzkHgeOJQwODEQwLBuXIqNIkJYkBiNpPvbD3fzrW86syf6e7Rh+LsI485m7T4xxfCSOKsvsMcOsaPLR6HUWyGKOS0sViT/T8S2ShN+l8uLxUR7b089VZywtqag5OBitq6PjfEweK5kNXmezj2b/xMwPFf1NK7c593N2ozuArbh5xVrFfdqVxNq24pckFJxTn84mL4eGkzOK11o56q+FLBS10IZiEOJXUBPUe3DHdMyUPH8gkiSeNvG5lLq28tQt4+mPEuEhDhltxMIGlmUgy+DXlrDWGMSbSX8kz91DLHMc6FZdHDnlCF+vKmf726VKGJbFWEKvyf7OHMOPxvW8G7S3bV3Bs4eHi/JPzf1MjyqjyjKaIhFJGhw4GWF9ezArgAtNiVWqQhXTpegaTegcH4kTTRqkTYtPP7qv5D7b4UQNpQebA/nGykA4SUI36RmK4dGUbL9mmO9vKmrtWLnNuZ8H90JilKMxlX/ekSQYcOGfg3itlXRutVCkpRbaUAxC/AqqzkII7piJ6aKDu5r9WHaMpQ2eurXy1DWDe4n37uFQwk/UMnGpMooiYdo2kZTJQd3H2hOv4BvcC+1b5vw1mePAkXiaWNrApcjZyHfTtjFMG5BY4nfVXH/Pdqz76skIn33sVZp8roJPLiZ/ZizllICWJAmvJpPQTY6PxAl5Q0gUd1xaikIV+Y5vRxM6B05GMEynTLVLlQl51ZKf0DR46+voOJfpxkrQo+FWZXTLntCvGebzm+a0dshy9n4eODxEynyZ1hn8VGcSr7V01F8LRVpqoQ2FIsSvoKrMZlWq1LF/uS3P+ZLnj8Z0/umRl2cMEKhlK0+9Y8VHCEdjxMwWvO7TfaBIEl6XQjzlIhw9hSc+Mq/I4Mxx4PNHh7FsUCTQTYuEbmJatvOYLNEfSeFSpIL6u1InJZOPdTOpqnTLQpUkkrpJLGWyvs2VXfxnO7mY/Jl+t4LfpRJJGXglGZciE0uZxFIGfpdS9HHpfAtVTD6+RZI4PhLHMG08mkzSsAh6VFoCblqgpCc061oDdXV0nMt0LgCZ/h1L6kSTBrGUQWB8rMznN5Vi7ZiveK21o/5aKNJSC20oBCF+BVWjVoIFKmV5nlwla19/uGasBouR7riGZSgEFB2DqdfYr+jEDIXuuMbqeXxP5jjwwMkIp6IpEjakTQvLtrFtkCVnoxNJ6khInBhNANML3EqelOQe647GnWP/TKCeU6LZRpHAmJSdZKaTi8lHxZIksaLJx4GBCAnDwqXImJZFJKlzao7HpfOpSDf5+NbvUokmDRRZImk4KbpWNJ6er0p5QlOKo+NquZBN5wKQ6d/EQISEbhJJ6njneRxeqrVjvuK1Fo/6a6EaYy20YTaE+BVUjVoIFqim5Xm+E+9C9ZOuFAOeNUTlFWy2jzBgeydWfrJtmu0R9sirCXrWzEv8gmMN+eQ1W/jggy/QN5YCnK/TVBmvpqDKEmbaQpElnnh1kM5mL998pmeKwN22ppnv7zxesfGasYwNRpIcG0lMCNRLGRaWZWEBSX1qarjpTi7yWdsafRrr24IcH4kTSRqYFiQNi7OqdFyae3z70vFR0qaFS5UJelRWNPpozNmQlvqEZj5Hx9VwIcvMQz3DcSwgoZtZy26GRp9GZ5OXYyMJkobF8ZH4vI7DS7V25BOvTrYHODaSIOSdvfR4PR31C04jxK+galQ7WKDaluf5WA0Wup90JQj53XzX+6d0Jr9Om9HLmNJMWnLjslOEzGGiUoCfev6U9/vzj89iuWDVEm67ciN3PLIby7bxaAqaImNZNgndRFNkOpt9vHR8lI89EiFlWBME7u4Tozx5YBCfS2Fje7Ai43VDW5C1rX5++eoAts2EQD1Fcf6VJBiKpVga8hTkyzndpq/Rp9HgCXJgMEZXs4873ri5quWFM8e3j+3p59OP7iPkdVwdJoutcpzQzOXouBob+dx5KKUbnIqmGQin2NAeoMnnyr7Otm2ShsXlG1q5+fK1RJLGvDbspVw7JovXsZgBzbB5WQPvvGR1QdesFEf9wphRWequyMUXvvAFVq9ejcfjYevWrTz55JPTvravr4/rr7+ejRs3Issyt956a+UaKpiVatd+L8Z6UC4yE++WjhDhpMHxkTjhpMGZHaFpF6taTYJvWXZdFerY0BZE77iA/9TeTY9rHX4rSqvZj9+K0u1az39q78bouKCk/nqdzT5aAi6afBq2fTrPc9Cjsr49SEvAzalomtGEsyHzu1UUWcLvdoRXLGU490uFxqssS1yxqRXLsrFsG9MGG8fNIW04lmpVkbO+nBks2+bEaIImn4Zl2xPGQmbTF/JqdA/HiaUMTMsmljLoGUnQFnRz2/YNnNERqvriL8sSV52xlHM6G4mlp85TmROa9W2Bkvt1Zo6Ot61ZMusmYPJGPnfcdDX7splESnlPTp6HOpv9dDZ50U2LV3rD9IeT2X7tHo4T8mq8+9JVnNERKug3zUSp146tXc3cc+253H3tOXzsT88A4K63nlXUZmFyfwEFz4c7u4e59aFd3PbQi9zxg5e57aEXufWhXXVV0KTeqCvL70MPPcStt97KF77wBS699FK+/OUvc/XVV7Nnzx5Wrlw55fWpVIrW1lbuuOMOPve5z1WhxYKZqGawgGXZvHx8jLF4Gp9LwbbtKQK4UgFnxVgNqm2tno56tESftrzH+af4Rs4L9dMkxxmxfLyQXEqDz80dJfbXC/k0Ql4XQY8z9eqmhabI2aT/g5EUumnRGnBNGY+GZSPLEkndmhA0lGHe49WysimgLHeI/axgLGFiWtDsd6GbFvG0Rdq0kCWJBq9Go9dF31higi/nYDRF91B8PJjP5h+++9KUsVBPR8W16Nc5mUq7kE03Dy0NefFoCvtORjg2HCepm7jL0K/lWDsy4lVf4uXRPcyrP4uZD2sl6HuxUVfi9+677+Z973sfN910EwD33HMPjz32GF/84he56667prx+1apV/Md//AcAX//61yvaVsHsVGtRySbX7x1jMJpmJK47vnxNE335KhlwVmiAQC34SU+mnifvXBH2yoBGOuX0+ZblgbKIsHUtAdqCbvafjLCiyUujV8v2o23bnIqm0BRpwpFxBk2WUWQJ07LRzak+tvMarzlV7hKJOENJiT6rgx9of8xueTORpEFns5eAW5si2FWZrC/ngYEIw7E0siyxpsVHa9Az7Viol6hwqH2xXmkXspnmoUafizOXNTAYTXPzZWs5a0Wo5P1ayxuSYubDWjVmLAbqRvym02l27tzJhz/84QmPb9++naeffrpk35NKpUilUtm/w+EwALquo+uFTRyZ1xX6+sXM2R1Bbv+j9Tzw7DEOD8YYiyVxqQrndAS5blsnZ3cE53UdJ/fFrmMjfPaxVxlLGCwLukin00SSBmldp+dUGK01QMirYds2Y7Ekm5c1sLrJUzN9ORJJYJsGAZeWrUSUS8AlMRYzGIkk0Jd4y94ey7L51tNHiCfTrFviHZ+8bdxumQaXh2MjCb799BHOXBrANJ1j8Vq5lhnO7gjy72/dwsHBKOGEToNXY11rAFmWStrWXcdGeODZY/SORIklUuyNJwl4nEAglyozFE3T4lcJuCRM08CjTJyeQ26JBpfjYuBRbNSc/p/LeM3eG93Pwa//FRJjRLQmDiaDKGaSNVIvt1gP8qD33fwo1sGxU1E2LwvSmhXmFrZtY5kmb9iwhPdeuprP7niVYzKsbfUhSzLTjYXchXztEi+Mj1XTNDDzn2RXnXKOk/muGQGXhF+TMQwdt2vqsp4yDPyaTMBVmjE92zwUdMuE4zYrQi7WLvGWpV/LtXbMpy+KmQ9lWWL/yQjdgxE6GjQ0ycZxKhpHgmVBjaODEfb2jrChvfbS25WbYvuimD6TbNuubce8cXp7e1m+fDlPPfUUl1xySfbxO++8k/vuu49XX311xvdffvnlnHvuudxzzz0zvu7jH/84n/jEJ6Y8/sADD+Dz+ebUdoFAIBAIBAJB+YjH41x//fWMjY3R0DDzyWfdWH4zTD5iyeerOR9uv/12brvttuzf4XCYzs5Otm/fPuvFzKDrOjt27ODKK69E00SO1mqS2xdHhpN85OHdBD1O0vUMY0mdE6MJogkDw7JY3uTjjGUNXLetk3M7m0rWlozl7/BgLOsHtqbVz/VFfI9l2Xz44ZfZ1xems8k7xdft2EiCzcsauOutZ5XkmMyy7LyWrgzPHx3mkz/aw/ImL0qe+9C0bU6MJPjYn57BOcuDi/K+yPTZ3r4wK5scC2cs7RSK0A2b4ViKDe1BPv/n56GqcvZ0IpwwWBJwZY9zh6JpGrwqbzp3Oc8fHZkwjta2+oser9l74+QX0VweYraHvf1jqOPuFQAuK4nHiPJJ6QPsSiwlbVlosoRLVVgScHFmRyj7vcWMhfNX1aYbzEzMdi/Mh1KsGbONm3+4amPJ5rNKz0OVZD59Uew9sP9kJO+alCGWNogkTe5865nztvyWYv2pNMX2ReakvhDqRvy2tLSgKAr9/f0THh8YGKC9vb1k3+N2u3G7p/pNaZpW9I0wl/cIyoOmaUTTCWK6RVPAg5GTlMnvcbN+qZtIQqd3LMH7XreOt71mRUkn7Z3dw9z1swNZP7CmgOML+VJvhO6fHSjKL/aGS1bzqZ/s5dBwMo+vm4t3XrIat3uqz+hc2jxb0EZT0IukqETTNn731Ep1sbSBpKg0Bb3Ze2Gx3Rf7+sO8OhCn0e9hKGFNKBQhS+BWFQ6cStA9lmLT0gYuWNPGh/5YPX3tIzouVWHDssasf+l120qXFknTI2i+AHYyBYaOpilkTrJTho03HcYyR7HkDixsWhq8pAwbRVG57uJVXLBqCTC3sVAvzCWgcy6pq+ZzbxQybkpJpeahajGXvij2Htjc0URXa5BXesfoatambCL6IjpndoTY3DE/n99Srj/VoNC+KKa/6kb8ulwutm7dyo4dO3jLW96SfXzHjh28+c1vrmLLBPXCTKUsJZwSsyGvi7NWlDbFUqmDGmYLvjmvs4l9/eF5CaNCgzaKibrO+PwuNjLBSClD5tBgdEKhCNOGeNokmjJ47vBwNkhxtmCw+VRQyoiykYhTSc5W3GAk0BQPsuxYpzJWK1NPkLRVhiwv8XGnzXDSZNUSH6MJnW8908PWlc3IslRzpV5LxVwCOquV/aSSQYS1HgRYDYq9ByoRuCeC6vJTN+IX4LbbbuPGG2/k/PPP5+KLL+bee++lp6eHm2++GXBcFk6cOMH999+ffc+uXbsAiEajDA4OsmvXLlwuF2eccUY1foKgilRrcS5HhobpFrkXjo1w60O75rXoFjtZFjp512ogU7kJ+TQ0RaZnOI5h2RMKRagS2IpEQrf51asD3HBR1wSBu6EtmO3j/QOReQuZXFFmmwY3r4Vd8VbOShzA37oWv0slkjTwuhRSaYMl1giv2Ks4yApsG1RFIqGbHBiI0tnknTBuazkCf65Yls39Tx2hKXKACxsM4lKQXmnVjMKh2tlPKllatp4ydlSCudwD5d5E1GKGoFqgrsTvtddey9DQEJ/85Cfp6+vjzDPP5NFHH6Wrqwtwilr09PRMeM95552X/f+dO3fywAMP0NXVxdGjRyvZdEENUK3FuVxpiCYvcqVadIudLIUFaGY2tAVpb/BwaDCKz6VO3HQBumUT9CicDKcmLEClth5OHh8BlwaEecC6gpuTR+niECuDLexP29ipCK3WCCP4+Za5HdN2/IB9LhVVgoRhMRhNE3QrE8btQhsLx176Fdcc+Ryr7OO4hw0MNHpdK/ll8BoOebZMuRcWo5WtkmK7HpjLPVDOTUS1K6nWKnUlfgFuueUWbrnllrzPfeMb35jyWJ0ksxBUiGoszjO5W0Bp8gmXctGdy2QpLEDTI8sSr9/cxm8PD5EyTFCVbL7etGmhyhIrm/1Eknr2mpbaephvfGRSVMWXnMt/D76H91g7eI09wBZfnIE4vGis4hv6dnaxAVWR8WoKWiYQbryqW8CtThm3C2Ys9DxL8/9+EskcIKa2EJad0tcrUwd5h/4lvtt8M/tdZ0y4F4SVTQBzuwfKtYmoxPpTj9Sd+BUI5svWrmbOWd7Ijn0n6R9LsjTk4cpN7ahqeap9V8LdopSL7lwnS2EBmp4LVzezNOQhktRJGXa2SlqmuIomS6TGr2k5rIezjY/B0Ll8LHEG//U6D6v9BqOn4LM/TxBOmbgMC79LJfddsgS6ZbEs5Mk7but+LFgWPHcvLiNMn7wMVVJQJImU5GVA6qDN6OX1kR/ycnD9hHtBWNkEGWrlHliovvjzRYhfwaIj33HyT1/uL1swSiXcLUq56C6UyXIu0fbl+r4NbUHOXtHIKyfGWBJwYVh2tkoatk33cDx7TcthPSxsfNgMeNexetUS3J4wAe+LBH1wbDhOQjedIL1xi3XSMFFlibdtXV5/Ft1CGNwLp17FFVqGXzezftAASBJjSjPL0t34wwdo6zwney8sJCtbpe8fQXlYiL74pUCIX8GiolrBKOV2tyjloluOydKybPafjACw/2Rk3ql7ZqNc0fbTCYLZvi/3mg7F0tlrGk8ZU65pOayHxY6P3A3QurYAJ0YTxFImadMaL2ksc97KENecu6Kg61N3JEbBSCEFvKxoNjlwMkoibeJSZRRJImG78JkplvqTvCXnXlgoG8dqZasQlIeF5otfCoT4FSwaqh2MMhc/sELFRKkW3cz3GabNDRd18at9AxwajM1rsswspN2DEd7bBR95eDddrcGyLaTl2uBMJwi2rWnm+zuPz/p9hS5A5bAeZsbH7hOjtNhuJ+vEuCFzthRMYwmdVUv8WJY9nnTfoCXo5tY/3DBhLC4oweRtBNVJAdfoDbC+PcDx4QSxtEHaAp+UQNE8XHfZ2WzJ+W0LwcpW7WwV5WLBbMzmyILxxS8RQvwKFg2VDkaZbrIt9LOLEROlWHTzfd/aVj83vXYVyxt9c5oscxfSjgZHrAU9StkW0nJtcKYTBLtPjPLkgUF8LoWN7cFZv6+QBagc1kNZlti2ppknDwxyfCSBLEv4VGApHBiM0hTwzpqCKTMmXrOyacoGaMEJptbN0LIR+l6CZj+NXhehDs2pzGeY+GLDuFacx4pzLpry1nq2slXbQFAu6mVjVm6BXit+yLWAEL+CRUMlg1HmO9nORUzMZ9Gd7vv29IU5MZrgjjduLnrSnLyQapKTecXvUulq1sqykJZjgzOTIGix3Y6YlIACv2+2Bagc1sOd3cN8f+dxfC4FWYKkbmFaTraHRNrkpq0r5pyCaUEKJlmGCz8Aj98Bw0cg2IakeglISUgOQGCJ87ycP0i2Xq1sc7l/at2iWi8bs3oR6AsFIX4Fi4ZKBaPMNNn+64/3cOPFXTNaUucjJubqWlEO8TJ1IT2ddrBcaZ/KscGZSRAYlo0sSyR1i1jKSf013++D0loPc/t3Y3sQJIlYygDLAIZp8rl47vAw127t5OCp6JRxM5tYX7DpvVZug+2fgufuhVOvgjHguEJ0nAMXvN95fgbq0cpW7P1T64KtXjZm9SLQFxJC/AoWDaU4Tp7NyjHTZKubFvtORvj4/+yhNejGPc1CMV8xUeyiWy7xUo20T+XY4Mz0OzT5dAYE3bRm/b5irGSlsh7m69+AW0XFsVouCbh48fgoN93/PAORVNEiZkGn91q5DVZc4GR/SIw6vsCtm6e1+NY7xdw/9SDY6mFjVi8CfaEhxK9g0TDf4+RCrBzTTbajcZ0DA1FMy8YGmn0uFFnKu1DMJibcmkJkNMEzh4YA5n3MWC7xUo20T+Xwl53pd/jdCh5VIZI0UCf1weTvm4uVrBTWw9n6N21Y9I0lSRsWK5t9RYuYhZTeKy+yDO1bqt2KilDo/bOuJcBt33ux5gVbPWzM6kGgL0QW5vZVIJiGzHHylo4Q4aTB8ZE44aTBmR2hGRf5jJVj94kxGsYLEzR41KxA2Nk9DOROtkr2vbZtc3wkjmHZ+DQFJDBtG79bpavZx1hC5/6nu7Esxy0gV0xMZjShs/vEKAORFF//3yPc9tCL3PrQruz3z4WZvg/mLl4yC+lgNDWl0mJmIV3fFihp2qfMBifkdXyKYykD07KJpQy6h+PZDQ7Avv4wzx4eYl9/OHvti/0dAB5Nxu9WGIqmp/2+F46NFDR+ysFs/XtsJIFtw4omL363iiJL+N0qK5u8DERS3P34fvb0jk17jQrt53UtgYKvuaA6FHr/HDwVLViwVZNyzW2lJN+akYtHU0gbZn2enNQwc7L8GobBE088waFDh7j++usJBoP09vbS0NBAIBAodRsFgpJS7HFyMcdS+axgsZRJLG3gUmQsG2RJQlOcfWe+nf101pfRhM7+/jBJw6LBo7GmxU/KsOZ9zFiu3KSTLe3Lgs4CE0sb9EX0sqV9ms1fFuDWh3ZxcCCKruusl0+wMWTyh6/ZwJZzLsJCmjI2ZjoxaG/w8LatK3j28HDe7zuvs4lbH9pVNSvZTP0LEE3qBD0aAc9pATAa1zk+EieSNBgIp/jrB1/gzI7QnDONXLimmdu+92LN+oYKHCzL2ZRfc95yfrl3gJPhZF5/82cPD9W8RRXqI+/ygj85qVGKFr/d3d380R/9ET09PaRSKa688kqCwSCf+cxnSCaTfOlLXypHOwWCosj4Vo5EEtm/cynmOLmYY6l8k61uWeOiF5KGRdCjTpjkJi8U+cSEW1M4eipK0rDwagqrlvhRFRlVkectoMqZmzRXiHYPOlagSNIse9qn6TY4GQvsaFznD9yHuNr6EUuT3cjRNGaviyPPbeQR7Y3siKyaItJmEtTndTZx3spGXjkRBmBLRwObljYgyxL7+sNVPdacrn9ThuE8L0msXOLPli92XHQiGJaNS5WxDROPKs8508iFBeZBrhS1np2gWuRzy2lv8PD6TW1cuKZ5wnWqF8FWD3mX60GgL0SKFr8f/OAHOf/883nxxRdZsmRJ9vG3vOUt3HTTTSVtnGBhU65FKHcSt02Dm9fChx9+mRsuWT3jIjtde4rxG8s32cqSBDbEx0vErmjykfsr8y0Uk8VEZDRBNGXS4NFYtcRPY85rSyGgypmb9LzOJryXK7xybAT6RvjXt2xhy/Lmsi84kzc4uRb8N/iPcO3IV/BZUcaUZtKqGyMVp6nvJbbLhxlp+kt6ms6aItLuufbcvII6Y0nOZ9Uci+ukdAPDpTAST6PJjptEZpGrhJUsX//6Nef0oT3kwT1+EpHrouNVZUwbFFkm6NFYOodMI7XmGzpdLusrNrXOOZf1QmC64LVjI3Ee2XWCLcsbyp6LulzUet7lehDoC5Gixe///u//8tRTT+FyuSY83tXVxYkTJ0rWMMHCplwpciZP4gGXBoTZ1xee0co0U3uKtXJMnmxTuoGqSFi2xLq2AI3e08J1poUiV0w8c2iIr//vEda0OBbfyZRCQJUjN2m+jcjX//coN1wiVXzRyVjw2wMab4j8EJ8VZUDtAEnCMC2ilosxu4118iBXJ3/M1wJnThVp1zZNENSFRLyfGE0wGE3TN5YCyTkB8Lscv99Gn1YxK9nk/g24JA7ufJItHSFe6o3gcykTXHSQJNKGmT2pkKDoTCPVtHpP3sxGkjp3PbpvQl8NRpL88tUBfr73JM1+FyGva9G5Y8wl20C9CbZaz7tc6wJ9IVK0+LUsC9Oc6jx+/PhxgsHq7/IEtU+5UuTkm8QVnPRTnU1eDg0n81qZZmvP7VdvLtrKMXmyPTGa4JvPdDOW0HEpcsELRa6Y+N7zx0kZVl7xWyoBVcrcpHPdiJSLjAV/rbuXjnQPY0ozumUTT+sYpp3NQnxCD9JkHSboPki4YcOMyf1nEw33/Hw/kYSBZYOFjU9VsGyIpAwODERY3xZgNKFXzEqW27+6rnMQuH5bJ90/O0D3cBy3ImNZYEs2Cd1ClaUJJxXFbrKqFW2fbzM7lkhj27BpqVOJbzSuZ4P9bEA3HZekWkrVVQnmmm2g3gRbreddrnWBvtAoWvxeeeWV3HPPPdx7772Ac3NEo1H++Z//mT/+4z8ueQMFlaMSvnDlzGk41+pEs7XnW7/t5saLV3LXo/uKsnJMnmy7lvjmvFDU0zEjzH0jMvkzSjkeMxZ8NT2Gik7YUImmdSbnHEjgosUa49TgSYbslXg0GVmSSOnGBJE223hrCbh58dgYDR6NDe0BDg44PtsuRcajysR1k1dPOgK4mlayczubsiJm94kxDMsCZILecet0zklFsZusaviG5tvMDsfSDEbSuFSJsYRByKtOce+Ip53x2dXsq5lUXZVgPhsUIdhKh/BFryxFi9/Pfe5zXHHFFZxxxhkkk0muv/56Dhw4QEtLCw8++GA52iioAJWq1FPOnIZzmcQLbU/Qo83byjGfhaKYY8ZamETn28/lGI+ZDcTxYy6SloqtJ7CZOlY8pEmjMWB4OXQygkuVwQZVkTgxmsi+brbxZlk2Sd1iRaNKk8/F+vYgx0fixFImlm0jIyFLEjdeXH0rWWZs7jsZ5lM/3kvPcJx1bQHHX32cuWyyKr1pm24zqyoSigymBcdH4yiyL+veIUkSigRp00I3LSRJXVS5Vee7Qal1i2o9UOuV8hYiRYvfjo4Odu3axXe+8x127tyJZVm8733v453vfCder7ccbRSUmUpW6innMehcJvFi2rNtzZJ5Wznms1AUcsxYK5PofPq5XOMxu4H4UYQ90WVs4ghR2mBC+KFNmzTGbmsV++0VYNtoskTKtLBsiW8+003XEh9bu5rzjjcbiKUMdNNiNJEGbHzjzzV6NULeUPZ5RZIYjqdZ3ugr+rfMh+kyociyxBnLQty2fQOf+okjgOfryzkf39C5bOKm23Rpiowiy0g4/RNJOq4oyvhLTMuekIKwVlJ1VYJ6O1WqBUppYKiHSnkLkTnl+fV6vfzFX/wFf/EXf1Hq9ggqTKVLK5bzGHQuk3ix7am2lWMm63EtTaJz7edyj8etXc3ccMlqHnzkKm7jm6ySBhiwQ6Rw4SFNqzTGGH7uN7fj2Gad9HRuVWZdWyBbkOS8zqYp421svGhKLGViWhaGZWPbEE85OY3BkdmBbP5nA3eF00Hlbo4w0/zlWvjytx/gDec5OY6R5ZL7cs7l8+a6iZtu0+VzKbhVmUjSychi4wQemuMCOG1OTEFYK6m6KkG9Ba9Vm1IaGOYy39XCyd5CoGjxe9ddd9He3s573/veCY9//etfZ3BwkH/8x38sWeME5afSpRXLaWXIN4kHXM7nHxtJEPK6pkzi9Wj1yCfAa60+/FyvayXG4/JGHz3+s/j3yA1cz2OslU/gZow0Gq/Yq7jP2M7v7Q3Z1wfcKqta/DR6NVyKPOH7M+Pt1ZMRRuM6lmWPByRKuFUJ04JDp+J4XSqNvtMZcko9tgpZEHM3R3/gPsRV+s84xQ38Se/n4YTN0EtbWHLF38DKbSX35Szm8+azicu36RpNOAU74mkD3bSxTZve0TiqIpPUTSQcy3AmsK9W7/tyUm/Ba9Wi1AaGYue7WjnZWwgULX6//OUv88ADD0x5fMuWLfz5n/+5EL91RqWjscttZZg8iY/FDGiGzcsaeGeePL+yLHHjxSv52COvsK8/QkvARZPPRcqw6srqUWv14eeyEYHSjMfZhGDIpxH0aBxIn8FtiXWst47RJMcZs/28ai/HsJ2jb1mCJp/G2StCWd/Xyd+/tauZ26/ezK0PvYBuOpk4bGwavCorGn3Y2LzSG+bVkxG2LGvA61JLblErZEHMl+PYjc4pYMy1FJJj+E68iP3YHUhXfQpWbiv5KUchn5fbzq5mL/G0RTipo8kyK5u89IwkZtzE5bPGHzgZwTDtbIVF27ZJpE0kyQJJwqXIdDb7CLpVYimjru77UiKC12amHAaGYua7WjrZWwgULX77+/tZtmzZlMdbW1vp6+srSaMElaMa0djltjLkTuIjkQQDe37LXW89C7fbNeW1O7uH+eYzPSR0k3DSYCiWRlOcSP1zVjTWjdWjWimlZqLYjQjMfzwWIgQzAmkskSaRVnjVWAmmU+kstxKgV1NY1eIEfWV8eSNJHQsIek63LehVafBo+FwKacNCliVa/C6CXg0JWNcW4NhwnMFoGllKl3SsF7og5stx3O9ySj3bkoyt+ek2PTTFhnH/7iuw4gKQp6bUy1Cuo9dMO72azJ6+CLG0ka2O6HeptARcs+YZzm66huKMJtLohoVbU0ibjvvK+rYAsgRHh+I0ejU6Gr0MRtMcH4kvemtnNdy66uUYvxwGhkLnu6BX5UtPHK6Zk72FQNHit7Ozk6eeeorVq1dPePypp56io6OjZA0TVIZqHftPEKixNKMJnSavC79bxbLsed/AmUlcX+Ll0T3Mery6tMFD1xI/I7E0p6IpvJrCDRfVzwJYq+VGi9mIwPzGY6FCMCOQjo/EAYgkDWIpAyNH+LpVmY1LgzR6teyxeTRpkDad8tJffOIQ77l0FVu7mnnuyDBHh2KkDaeMNcCx4QRBj8qa1gCtAacdN1+2lpXNp6uIgVMEYq6LfjGWqHw5jsm5tookkbYlku4W3IP7YHAvtG/J+73lPHodi+uMJdJEkk5/uBQZZdw3N5IySOhO0Y2ZNnGZTdd//uIgxw8nkCQwLMend8V4cGHPsOObPZYwMGybrmY/r9/cxoWrm2tWfC1E6ukYvxwGhkLnO2xq6mRvIVC0+L3pppu49dZb0XWd17/+9QD84he/4EMf+hB///d/X/IGCspLNYMdZFkiljJ48LljFZ/8phMOrUE3LQFXNr/v1q762EnXsu9yIRuR3NfOZTzOKgSH4vzXLw/ygdetocnv4ryc3LYHB6JEkjqmZdPe4ObSdS08dXCIsYROyrDoGYqhmzZIjjW4s8nLnvFCHW/buoKvPXmYpO7kiFUyQSm2zVhCZ19fmFUtftyqwlkrQtmFqRSLfjGWqMk5jtPSxAXctG1kGWTNSyo6xKHDPch25xQhONMG419/vIcbL+6aV5ngoFclMr7J8Gunx7EqgSLJxHSTSNIg6J156dra1cxfXraGQ4NRlvhduFUFv1thLOEUFzEsG5cqYxsmXk1xyvi+cIItHQ11cb8vBOrtGL8cBoZC57tI0qi5k716p2jx+6EPfYjh4WFuueUW0uk0AB6Ph3/8x3/k9ttvL3kDBeWnWsEO1Zz8as1Hdr4spIjtuYzHmfpzLGkwmkhz/FCCg+M5m9e2+rliUxvXXdiZPXVo9J8WbFdsGuYbTx3l1/sHSeoWbk3G73Ysh40+Ddu26R6K84VfHmQ4lkKWGC+WYY/njZUwLZuEbtI9FOf1m9qyG49SjftiLFEXrGrO5jjW0XDZKRI5OY7ThoVHk+kbGkVJWXzuyZOceO7FCYJ8pg2GblrsOxnh4/+zh9agG/dcN7G5FUcm9eOEvydXJslDk99F0KPh0RT8bhXbtqcUtlBkmaBHY6k4Oq4otRagWwjlMjAUMt/t6w/X5MlePVO0+JUkiX/7t3/jox/9KHv37sXr9bJ+/Xrc7vwTsKA+mBzsEPSoIEEkYbCvP1zyo8BqT37zOcKqVR+1zCT6jaeO8kpfmJRu4tacSbQWjxFnotjgm+n6czShc+BkBN2wkCRY4nehWza/enWQn+8doNmvEfK6skIt8/lbu5rxuhRe6Q3jUR2B5HefXvAkScLvVjk2EkeWJLyaTNKwsG2bjDKTAMt2yuZevrE1W4CkVOO+GEtUZnN054+jHBxZzkbjCAnZWaQTaRNFgpRu0myd4ph7PcaSTTQY9gRB7nereTcYo3GdAwNRTMspEd3sc6HI0pw2sZGkQdCjEk7oJHTTcXuQnY1E2rTQZImgx7EOz8ZksRJLmdnCFkgSacPMpjeToO42vPVMPRofymlgmG2+q+WTvXplTnl+AQKBABdccEEp2yKoMpnj6Z3dw3zp14fL6opQ7clvrkdYdeOjZp/+zxFk9UcxwTfTFZw4PhLHMG3cmoJhWaRNx/pnmha2BLppE3QreYVaJGEgS9DW4Mm6M0xon+SIWwnHR1iRJRK6mRWB0vhrgh6V5Y1OAaD5jPvJm651LYGiFsStXc185E+28JtfvINlJ/6LRr2PY0CDW0JOpwjow+hakN80XoOsKPgVJz/u0aEY//WLg7xuQyuRpE5rYGLKtow11acpJA0L07ZpcGtz2sSGfM5mpNHn4lQ0RSxlkjYtZMkRvS0BN7ZNQRauyWLFrchYFtiSTUK3UGUpm94MxNFxJanFAN1CKOcp6UzzXa2e7NWqIagQiha/sViMT3/60/ziF79gYGAAy7ImPH/48OGSNU5QeSrlilDtyW8uO+la91Gb2j5ncsz4p1a7feUkX3/GUgaxlImmSNkiBqeiSQzTqbpmWjbxtAFIdDX7pgi12TZImSwE0nhAlqbIqLKEaTvFLSwbDNOiwatlxVq+cW/bNrGUiW45Ii+lG1PG/XSbrm1rmjk+Ei94Qdza1cx577mBYy8tx73rfgDWaCP0x5Mcc6/nN43XcMhzOtBtLGEwljB4+vAQe/sjjMTTxNMmq5b4afRpE6ypzvU4XSVtLpvY3H7cvDTIUCxNarzIyBK/i2MjiaIsXLliZfeJMQzLAmSCXpUVTT4avadFtDg6rhy1GqBbCNVKCVdruZjrxhA0DXMKePv1r3/NjTfeyLJly6ZYLwT1SyVdEao9+RW7ky7ltSnHbrnabiTVJl9/pnQTw7IwkdAUiSV+Fz3DCVyqnLXKGpbNcDwNkouWSUJttg1SLGXQGnAzkkiTNi0USUaSJNTx1GjxtIGiyBPE2uRxPxp3MklkUnphg6pInBhNZL9rpk3X8ZE4b9u6gmcPDxe8IMqyRNe5r0fffCn87GccPv+jfP6pAYwlm5AVJfs6x50hgm7aSBIsDbnRTZNw0nl8fVsQGzu7CUgaE6ukgbOJHYokSJ94GZKAtxFaN0+bRi3Tj7c//DLPd49iWTY2NhISR+Q4HY2eoi1cGbGy72SYT/3YKdu8ri2Qzd2c6U9xdFw56v0Yv1qVPmslF3OtG4IKoWjx+9Of/pSf/OQnXHrppeVoj6CKVNIVoRYmv2J20qW6NuXaLVfbjaQWmNyfkaSObYPfrbBqiX9cqNkosow+bvU1LZtjw3H6xpL4XDKaImetrrNukHwa7926mvuePkr3UJyYbuJRFWzbJmVa2DZ0Nnom+BLnjnvdtDgwEM2m9JIlRzAbpswXnzgEwJvO7ph1U/PsoSE+cNka9vZFANjS0cCmpQVkLRgXoHLXRZx4/hUaDBv/uPbNdWdwKRKmLeFWnbzH+/vDJHSTo0MxVi3xgQ3xcf/cXDcCgJWxl3l36hE2PD0Ekg6qG1o2woUfgJXbZmxexl1Hyn7i3N13ZFnijGUhbtu+gU/9xBHAtXJ0XKuU80i7Fo7x6/XIXpYlNrUFnHSEiVEYbJxxQ1lqFoqhpWjx29TURHNzbSt6wdyopCtCLUx+UPhOuhTXppy75Wq7kdQKuf05GtP50q8P0TMcI+RViaVNx63AsEiMW1pVRcLnUrBsCCcNJODEaBxYkv28fBuks5YFef/mFFuajnPu5Rqffr6RF0+Es24UHk3mnM4Qt/7hhgl9mhn3//rjPew7GcEc95W1bIinTUwLkC2ODsX4+P+8wg9fOEH3cJylDZ7sIpPrJoFt88T+QXb3hZFhTpupda1TfYdz3RkyLiOZwLANSxs4eipKNGVwMpxEVSQsW2JdW2CCG8GaxG6uGfkyLWoCd2AlaF4wEtD3Ejx+B2z/FNaKC6f4Md/3dDeGaXPhqiZiaTMb3BZwKwzF0vNaWGvt6Hi+lEvAVeJIu5p9MdPvO7ujNq3NWXqehefuhVOvgpEqakNZChaKoaVo8fsv//IvfOxjH+O+++7D5/OVo02CKlFpV4RaWYgKOcKa77Up92652m4ktURuf2qqlN1gtQTc+DSZU7E0tu3k5PVpCrIkIWEjSxKyBE/sG+Sac1dMyPyQu0FaGn6RlQe+gPSss/hsUd3cv2QjR8+/nufNM4CZra9bu5q58eIuPv4/e7AhmyXCtGwUWcKjOebXtGGxpy9MOGnQ5HPhdzPBTUI3bXTTcjIs+F2sXOKf02Yqr8uIYWJYNqZlok2y6Ia8Gqtb/PQMJ/jTczpY2xbg27/tYSyh41JkPJpCKq1z0dDDhKQY7rb1SJlsQK4ANPth+AhDT/wXn1Rv5cBgPCtA2oJujg7FWNrgIZw0J7iEyBK4VYUXj4/Oa2GtlaPj+VIugVrJI+1q9MVsv+/2P1pftu+eNz3POhvHxCgE20GduqEstwBeKIaWosXv//2//5dDhw7R3t7OqlWr0LSJi+nvf//7kjVOUFmq4YpQywtRrlUl6FFZ2+pnT194Ttem3LvlWnAjqRTFWLsmb7CQJGzbCVLzqE6AmmHZpAzHKtzid7G7N8y+k2HOWBbKfk5WUPc8C8/fOWXxkfpfYvVYN6sLXHyWN/poDbpp9rkwx3MGJ9ImXpeCxPiRvwRLAi7GEgY9w3FkiaybhCZLpG0n2Ni24VQ0xZKAm0bv3LIszOgy0nLaopupdhdJGBiWxWOvnOTM0SRvP3+i3/EG6RgblV4ampbT4Ju0SEoSYa2Jse7dRF0v09C4MStA9p+MjJcYlzkZTk6p8hZPm0RTBs8dHp6XValaPptzId94f+HYSFkEajWOtCvZF4X8vgefPcZltWjXsyzH4psYheY1p/Ne52woKaA0+XxZKIaWosXvNddcU4ZmCGqBarki1OJClM+q0uzXUGRpTtem3LvlWnEjKTdzsXblbrCeOTTEF584iG1DQjdJjFtdnbLENgORNIZl8akf7+W27RNdFkq5+IR8Gm5VQZElZBxXjEwgHjhCT5agweMi6EkRTqQ5MmTnFGhwLMW2DS5FwrKctG4hbwgkCb9L5cXjozy2p5+rzlhasADOLTn+5V8f5thwnJDHWSZycybbEjT6XLQGXNnAu9v/eBNBj+ZYx0fTLH9aRgpMva9t2+ZY2CZgpVnfYHBgfAH1u1VWNHk5FU3TPRTLWuZzq7zZikRCt/nVqwPccFH9j+fZyDfe17b6GYmnyyJQF8qR9nQU8vsODca4rKtKDZyJwb2Oq0OwPX8BmGAbzFKavBQsFENL0eL3n//5n8vRDkGNUCuuCNVkumOxvrEkiiyxLORlOJYu6tpUYrdcrb6rVODIfI5jczdY33v+OEG3AkiMJNL0jiSQJHAp8niQlUzPcHzqZ5Zw8cldQBo8ajYQD5wFJONnG3ArrGz280rvGOGEgVdTQJIwDCvrCuB1Ob64sZRJ/1iCoVia6HiJ4E8/uo+fvtxf8FF47nVyqfIEl5FjwzHShoUsS2iyRGeTj4BHw+9WnXLgz/TwuWvPdfr+5HLHF9FIOJuDHGJpEyMdx1JcxJWJC2TA41iuRxM6QXXSwgrolk3Qo3AynKpbAVYo0433F46NMhRNsaY1UHKBulCOtKejkN83FktWuFWzY1k2x06coC0ex3S14LftqZm2VC8YA87mvIwsFEPLnItcCBYuteyKUE4sy2bfyTB3P76fgUiK9TnpkHKtKs1+Fx954yYiCaPga1Op3XKl+65SuR5LdRyb2w8rm7wcHdKxAK/qVP1K6BZBr8q6tgA9kz8zMToeYOLN/+FFLD65C8hgJAXjOYElyclJrMoSKxqd3+lWZZr9LsIJA8t2SiZnfJY9moImO6nVkuOllDPPuVSZkFed81H4hBy5vWOMxg3U8QprmTLPMI3gat3sBOH0veRYxXPGu26YNFqj9Ho20KutmvCdEtASdDGW0EkZJoosTajwpsoSK5v9RJJ63QqwQphpvLcGXJwMJxmMJGlv8DB5tM9HoE7epEu2RYd+FL8VJSYHOGCtqIsj7eko1AhRS2TmWKPvJLdFLWLxQRR3kBXNXhq9pwvOYCScDae3sextWghGsqLFr2mafO5zn+O73/0uPT09pNPpCc8PDw+XrHGC6lGLrggTsKzTqV5myR1aCJkJZvcJ5whXlWX2mOEJifAzi/zBgSiyJLFtzZKCP7+Su+V8fVcO62wlA2NKdRyb2w8HBmNEkgYuVca0IW2Y2apfcr7P9DZOa80Eil58cstR/3r/IHHdxK3KBD0qS/wubGwiSZ2haJrNSxvoG0tgjmf7cqsyA+Ek0bTpBMvZTs5icKqyZXLutgTctMCcj8Izm6nv//449+zYz7JGLw0edUofTBFcsuxEnz9+h+MOEmzL+kf7Yn30SQF+6v0TbGnqPevTVFRFwutSMMZFb6bC24omH5oskapjAVYIM413l6KgyTLRpEksZRCYJOLmc4qUuzk8y9rHG6I/pCPdg4qOjsZBezkvdbyDDW1/MK/fVy0KMUKc0xEERqrXyBxy59j2wBoGjVV0pg5yLOHhwEmT9e0BRwDbNkQGoOMcZy2sAPVuJCta/H7iE5/gq1/9Krfddhsf/ehHueOOOzh69CiPPPIIH/vYx8rRRoFgIiVO9ZI7wThBUDKaIhFJGhw4GWF9ezArgOdjVanWbrkc1tlKB8aU8jg20w93P76fgXAK2zBRZDkrrqbt62msmZmCF/JoH3rbWQRbNlHoNiyzgDyy6zhffOIwY4k0uuFYcE3bxrKcoLPXb25j/0CEwUgKdTwncKaSWsKwMCzHd1lTHOGbazkG5nUULssSZ60IEfK5UGUpb2GjvIJr5TYn+jx7rw6A6sa14jweC1/OUyOddE06vs1cy7agG7ci0xJ0OwF+iuxY6myb7uF4XfgUzoeZxrvfrRDwqIzE06QNE3LE73xPkTKbw//vke9zzeBXaJRihJUlJHAhGQk2SIfZlvga8vENFUmrVWoKMUJct62T3pePV7upeefYX3EN7xj+El3WSU4aIU4MQahVQ4oOOpvuC95fsXy/UAdGshkoWvx++9vf5itf+QpvfOMb+cQnPsF1113H2rVrOfvss/ntb3/L3/7t35ajnQKBQ4lTvUyeYGIpE1l2rIleTSahm9lAIon5++ZWwy2hHNbZUgfGzGaZLrXPdEYA//WDL+BRZYLjvqu5v2TKZ+axZo7qCgPDY3hSp4jg5+v2pejffamojYUsS7z1NZ0kdIvPPvbq+Bh0jvv9LgVJgm8/24PPpaApMpZtI0kySd0CbKf0gy0hSWBhT3FLgPn7as7ZbWflNicAMOeURmrdzOuOjfLkLMVDvr/zOEOxdPb5eMqoK5/C+TDTeHfuLxeRpMGpaBq3quDWFEbG4xBCPm1ewYBbOxtZ1fhrjFiCo9ZSLFNClsHvDRJsaiWQOFGRrALlYjYjxNkdQXpfrnYr88+xhzxb+G7zzbw+8gjtqW6U5BipaAOejnMc4VuHG5JqUbT47e/v56yzzgIgEAgwNjYGwJ/8yZ/w0Y9+tLStEwhyKUOql8kTjN+t4HepRFIGXknGpchOwv+Ugd+llMQ3d/Ju2bJs9vWHSy6Gy2mdLaUlthDLdDl8pjctbeDMjhCv9I7R7lKIpQx000JTZHzT9XWONTPeu4fIWAQslUPqWn4eeBPHPVs4NYeNhWXZPHt4mEavxvq2wHg6MxmfS2ZPXwTdtJAlhU1LGzg+GieWMgEb04LWgIs/v7CT/2/nCUJex9Vh8oZkvpu2ebntyPKUAMBCTkE2tAf4718e4sipGJZtE3CrdeVTOB9mG+9Jw+L8riYafRovnxjjVDQ9PnYdX+9v/rYbWWZu12lwL0sSR7GXrcSPJ3tP+DPtUCuTVaCczGSE0PXa8CWfbo495NnCYfdmlqaOEhs7xV9cci5nn3dxXW5EqknR4nfFihX09fWxcuVK1q1bx+OPP85rXvMafve73+F2518IBYKSUIZUL5MnGElyfD4PDERIGBYuRca0LCJJ3bGqlNjqVM6AsXKmLSqVJbZQy3Q5fKYzn3n7wy/zu6MjWJaNjY2EhCxLdDR68n/mym1Yy8/nk/d+lz6jnzHbzwFzBVJawe+OsbzRy1hCL2pjse9kmN0nxvBqChISjV7HrzaaNIilDTyqQjxtoSoSWzpCWaFumE76szdsbufAQIxXesdoGf/MTCW4tGkyGE3zms7GeW3a5uO2k8+yP5MA2dk9zDef6WEgkhrPhCHR3uDhhosWvvCFwjYbt165Hsu2+dgjrxD0OIFwTT4XKcOa38nOeGCnFPASkPMEf1Uoq0C5qfUj+5nmWFuSOSitJOzpwLX8LCF850DR4vctb3kLv/jFL9i2bRsf/OAHue666/ja175GT08Pf/d3f1eONgoEDiWMts+Qb4Jp9Gmsbws6yfyTBqblVOE6q8RWp/m4JBQSwFbOtEWlsMQWa5kup8+0k+IMpKzjgz3j6x95sZcf9jZi2414NAXPeEaCSNLg4ECUzmZfwRuLnd3D3P34/mygpSyD3+X4H9s4OYg9qkTSsNBNCwmyQU6mZY8XnUjzl5sSPHhyH/2DHvpdqxiIGUSTBrrl+AAPx9O8cGyk6Os0eazd/WfncPBUtOCTitk2eJOvz+T7oi3o3BfHRuLc9dPSBlLO9lurGcAz23g/r7OJWx/aRcqw2Lw0eDof8vjJxZxPdkoc2CmYGwsln26tUrT4/fSnP539/7e//e2sWLGCp59+mnXr1vGmN72ppI0TCCZQwKRsK26OxlQGDg8R8mmsbvLM+JHTTTCNPo0GT5ADgzG6mn3c8cbN05arnQvzcUko1FpcztzCpbDEzsUyXUqf6UwfGKbNhauaiKctdMvKuhv0jCTy9oFl2Xx/5wkM08bnUrBsGywnvZhXVkjoJoORZLbgw0xkhN5AJJUNtJQkiUjK4MBAhBWNPmQJdNMpv5wJcsuQ1E3OYT+bnvk6oehh7rDjnNRhd3Qp91vb2S1tosmn0Rr00DeWLNoaON1Yu/HilYR8zu/bPxCZtg+K3eAVcl/c99RRvJpCJFl4qsH5/NZSp+0rhpnG+77+cHlOdmZIU1eNrAKLlYWST7dWmXee34suuoiLLrqoFG0RLEKKsrTMMiknRvp4xVrFP+9IkjJfxqUqbGzzcfkMpSpnm2Dagm5u276BMzpC03/IHJirS0IxYqLcloP5WmLH4jop3cBwKYzE02iyjN99up3TWaZLdVyZ2weyLBPwTBSW0/XB/oFI1g81kjIAZygqkoxXU3ApThqqgEebcWORK/TWtwXYY4aJJA28moxXkkkYFqdiSXwuhZG4TpNPm7CJsW2b1rFd/LV1Pw0jOgTb8fjbSfWe4kzjKJ90Pci3Qx/gRPDsbMnk3E3VbEw31nZ2D/PkgUFCXg1VlqYViXPZ4M12X3hUmSf2D7K7L4wMJROolUzbVyzTjfeynezMkKaOyEBVsgosVhZCPt1apSDx+z//8z9cffXVaJrG//zP/8z4WmH9FRRK0ZaWGSblxEgf3TGN+7QrCQZctI4L2H19YS5fC7uOjXDBmjZgquA+r7Op4hPMXBauYsVEJSwH87HEnhhNMBhN0zeWAsmpVpY57m/0aWWvET9X8fDc4WFORVPZvx0JIGFYFrG0jVeT0S2LZQ2eGTcWE8R3xtf8ZISEbuJS5KyI9nucLA+aIhNPGdk+PBVJ8DHzpyx1J5Ga14MkEUsZjBoaqracZVYfb0z+mK8GzsSW5CmbqrVLpnEfYvqxppuOa0dCN5ElOHN5Iynd5JUTY/zTD3Zz3YUruXBNMxvagnPa4M3UJ6NxnWMjCRK6iUeVaQt6SiJQq2ltng9lrRo5TZo6RFaBilPv+XRrlYLE7zXXXEN/fz9tbW1cc801075OkiRM0yxV2wQLmDlbWvJMyrbi5hVrFfdpVxJr24o/Z/FqcHmBMA8+e4ytq1p54djItIL7nmvPrdgEM5eFa65uAuUW9nOxxDoBTd1YtpOey6cqWDbZ4/71bQFGE/q8LNPlSJ9mWTa/3DcASHg0mZTh5NeVsJFxfHBjaadYxdu2rphx/EwWeo1ejfXtjq95LGViWham5Vjw//jsZTx7eHhCH/5hywjnhwfxNnSAJGHbNuGEjm7aKKrEmNJMR7qbDv0oJ1xrgEmCfgbxm2+s2bbjX2xYNj5NIWXYJHUTw7KJpHRGRww+89g+Opt8rG8Pcn5XU9Gbi+n6JPPdadMJQg16NCcVXAkyl1TL2jxfyu4TmidN3XyLCQnmRjWC82rJ/70cFCR+LcvK+/8CwVyYdwquSZPy0ZjKP+9IEgy4ssI3QzY/4mCMR3ad4Fu/7a6Jo825LFxztVTWmuUg0/9jCZ0N7QEODkRJjmfW8Kgycd3k1ZOOAJ6rZbpc6dP2D0QYiKQIehQSuuVUU9NNTMvJtytJjlvk5qUNXHPu8hnbmDfY0qsR8jrZHCJJnaRhcccbN3NGR4jrLlg5sQ8TLyH/xADVy2gizfHhBJGkQXo8MC4lyQSUNH4rmv3OQq2B+cZaLGUSSxu4FBlFltB1k5F4mv6xJIZp41ZlLGw0ReKV3jEOnIxgWHZRm4vp+iTz3QABjzrh8+abuaRQa3Pmuy0LXjlRG+4QZfcJzZOmTrDwqUX/91JT1BZO13WuuOIK9u/fX672CBYBxVgwpyUzKa+6lAHvOlKmjUebviZ72jD4/s7jWcHtd6tZy1FXsy+bmsqyZo7yLxWZhSvk1egejhNLGY7VMGXQPRzPu3DliqV8zCRsMpaDbWuWlDRwby4cHIxm+7/J52J9e5CgR3WEkmEhIyFLEjdePLeJNnOqsPvEGA3jVdsaPGp2k7Oz2ynBPpc+yAillUv8qLKEYdl4Nafilk9TnDyrisQ1r1k+6zXOCL3BaCqbbQJAAvwuhdR4hpGMmJvSh74mUN2Eo2EOnIyOl2qW0JTxqH87RdRU6Eu7iSYNhmMpjo8mWNfqn9UamG+s6ZaFZYMiORZuWZIYiqYxTBuvS8GlSNi2k22gq9mXFeEDkeSE3wenNxfr2wIT2jJdn0SSOinDQhsvPz35yno0hbRhzilzyXT3VcbanNQtLMumfyzJ/pNRDp+KEUnpnAwnKzpn5CNzsrOlI0Q4aXB8JE44aXBmR6iqwlxQvxQ6f9Y7RQW8aZrG7t2785a3FAgKpdSBGrMdXwPYSPSFk2XJeTtXinVJWCipb8KJqcf9GWunblookpOWa3njDJGK0zDX9GnfeOoor/SGSekmbk3hzI4G3n3pqil9kBlrbkWe4KJgjYvBgFsl6NG4cPXsomPelrvWzdhLNhI/8ByG0YZ3fOx7NYimdFrsUXZbq/jpyUYUeRTdsiekPDu7Y/pxkm+sabJTVtm0IW1aeDWFlGHiUmUkwLAdv21NHvcvDrrpDydxq0pBvy9zzGqYNjdc1MWv9g1waDDGqWgKywavptDZ7JSftmFCURIgu/HLd1wLTHvyMZO1OZzUnQIjspS1eJuWTTRlImHy4vHRis4Z+ai1kx1BYZTaraAUn1fpsvXVpOhsD+9617v42te+NiHlmUBQDKUO1JhNFAK0N7g5Ppae1jo83/Kvc6WYhWuhpL5p8E7t/9zctbGUgXuOgTrzKuwhnf5vOlte7ljravYRyik4ocqOJfTM5YVvQIrdAE1e4Nxrryexbzed0kkiVjNpyY3HTtAsDTNq+7nP2E7KlpAti5BHpaPJl015dvsfrZ+2XfnHmoxbVQgndTyqzJKAi+MjCRTZ8TdOmxZBj4rf7dxjHk1BlSWu27aS54+OzPj78h2zrm31c9NrV7G80UfQq/LFXx1iT1+YkXiaE6MJZ9Nh22A7pUnWt/vZfWKM//7lQQ4NxrKf0+TTiKcNhmN6tlLc+vZg9gh3uvsqnEyPl5B2LPHq+H2lyhKKrBBPO+WFR2PVrwhW6wUbao1q+7OW2q2gVJ9XzsJItUbR4jedTvPVr36VHTt2cP755+P3+yc8f/fdd5escYKFSaktmDOJwrFYEprhzed28NWnjpUnMnqeFLNwLYTUN+taA2WzYBd7qjA18NIZN3v6wnl9OvONNacqG84GxFf8BqTQDVC+Ba7J5yegvIv3qDtYrvcQsIaJmgqvWKv4prWdXTgCV5VlTNv5/e1BN93DcR589hiXzWBcnzzW0oZJ0KNi2U5+Y4/q/O60YWHajlV5ReNpa1HmnrpwdTM3bOua9vdNF/y6py/MidGE4/O8LMR7Ll3F7Q+/zCu9YSTArcpgQ9ywsG3Y0xvhjh/sRpUlVi3xsaLJR/dQjH39YWwbNNXJoxxPOxbd4yPxbP/mu6+SuoUkgUd10tflIo1f07RpMZJIF9zXgupTbX/WUqfVK+XnlbMwUq1RtPjdvXs3r3nNawCm+P4KdwhBIZTDgjmdKNy8rAEI88azOnjiwEjduwxA/R9zTuj/oTh+t4osgWU7Vt+5CMgMxZwqzPWIL3esHTgZ4cRoAlmSWNPi55bXr53TAjrbBmi6Ba57OM5QYg0nWv6O80L9DAz002956ZY7iehONThFlvC5FNKmxfGROKGOEK0BN4cGY1zWNXO78o21SMLgm7917jNJkkgZJk0+VzZFHUy9p6b7fcX0wXmdTbQFPZwYSSBJnK54J0l4NZmEbmKZNoqscGwkgWHZHBtJkHE3tm0bbbwIiW5aQHKKC0zubz06FOOTP96DZTnvnTxnGJYT3NforfyGWTA3ChGKM7kDzZdSuxWU+vPKmj6vxiha/P7qV78qRzsEi4xyWDDzLdSrmzz87GfHF4zLQIaKHHNaVtnSHG3tauZtW1fwhV8d5PhoAst2fGZbAi7eu3X1nC0wxZwqzOeIb2tXM5YF//2rgySGYpiWzclIim8+04MsSSW1IM20wK1v9TMST3N0OIl3WSd7jRCqImPbNjaORVRTJBRZwoXsZE0YzxU8GI4DsP9khM0d0y+O+cba1i7nPnvuyDAPPttDyjBRZOgPO+4ISd1kWchb0ip/lm3TO5pgZbMXRZI5PhpHgvEqe2QzMmiyhG7ZHDkVw7BsFMn5rExcmld1CogkdYv9JyMT+jf3t4Z8Gq0BN6eiKRLj2UiUHJ9nRYaWgJsmv6u4DmXqsftslSgF86dQofiZt5Yvu0Wp3QpK/XkLJa6kEOZd4U0gmCvlsGBOXqh1/fTxzEJwGagYPc/m5FJOOQnuWzY6RUZKkOB+Z/cw3995HJcis7E9gCxJWLZNNOVk5di0NDhnC2qhm5z5HPHt7B7mrp86FqSlDZ7sd5Qjbd5MC5wsy6xq9nH4VJyj42LPpYBuOSnXZImsW4YiS84xfTzNUDSFrjupwz7y8G66WoNFHftm7rNNSxvY0tHAJ360hxd6nKA6cL7XsGz29Udm/MxC++C5w8M89ko/x0fiqOMbsJRp4lUVZMkpMJLBBhRJImFm2iJhk7HWWijjbgxJwySaMqY9wt3QFuTsFY3s7B7GMG1iaYP0+DUNulVUReKcFY1FC4HcY/dIUkeRJda1ePnTmS59GTeii4VCheLBweg0nzB/Su1WUOrPW2hGopmYk/j93e9+x/e+9z16enpIpyf6Oz388MMlaZhgcVDpQI16dxkoKdMtqD3POlX0EqMQbD9d2rTvJefx7Z+alwDOtcCsbvFPWIhaAva8I4oL3eTM9YivnBHRlmWzrz/MK71hALYsb5h1gWsNehhN6LQG3OztjxDXTRRJwqU64kgdb4Jp2di2zYmROGnTpsWnAjpBjzKjaJ8tOGhPX5hX+8NYtpPrN5PybCyh86mf7AXgndvy+1cU0geGZfPgcz1EUgaq7PjtGpaNZUHSMFFkJzVeBlmSMO3TYtgYz8EMEE+bpA0bjyZn07VNd4SbEQLHR+KMxtO0N7gnbNIafa6ihcDOo6f45v/8DCM6TNDw0mMsx7AlhsIJ/rQZvvv8Md558ZqJbyrzRrQUVDuArBAKFYrhRPn8WUvtVlAON4XFYiQqWvx+5zvf4V3vehfbt29nx44dbN++nQMHDtDf389b3vKWcrRRsMgp9cRaT5HR+cTQpvYS5OmdbkG94Cb43Vcd4du8xqnaAOAKQLPfKSv9u684RUbmaHnKzfNbrojiQjY5cz3iK1dE9M7uYT63Yz8vHR8bzzLg5K5e2xqYtVhEyOviX996Jp/92X72n4ywosmLacGBgUj2yD6lm5i2jWGD16XQ1ewDEvhdKl3NWl7RPltw0HOHh7jzJ3tJGbZj7TUtbFvCqykEVZVIyuALvzrItVs7UdWp42W2PhiIJJ1UY5LE+rYAe8ywk89YkZEkE8tm/Loo40NVGk9HlvM5Od9njbssZLJzrGmZOefx1KA/A5eqcNbyxqKFgNX9W+zvf4ZboodQLJ0UGkfl5XxPvppXxgMT//MXB9iwLMQFq5Y4byrzRrQUVDuArFAKFYoNXo2BMrWh1G4F5XJTWAxGoqJXrzvvvJPPfe5z/PjHP8blcvEf//Ef7N27l3e84x2sXLmyHG2cwBe+8AVWr16Nx+Nh69atPPnkkzO+/te//jVbt27F4/GwZs0avvSlL5W9jYLSsbN7mFsf2sVtD73IHT94mdseepFbH9q1YBJtz8TO7mHe9fVn+fN7f8sdP9jNHT94mT//8m9519efm9/vzyyofS+CJwSNXc6/fS/Bo/8Avb93FtrJAaySBME2GNznWIznyOk8v9OnnZtrwYJcZivsMZciF5BrQXLabwPRlMFIPE00ZeCeQ/t3dg9z+8Mv87ujI6QNC68m43OppE2LPX1hhqIpjo3EZywWccbSEH/zhnUsDXkYiqXRFIm1rQG8mpOWy7SdtjZ4Nda3BQnlBmpJEn6XyovHR3lsTz+WZc+a7P7bz3bzjw+/RFK3kCXHHUCSTpd4Ni0bj6pwKppmx76T0/bRTH3gVhU0RaYt6FhdVzT5UGUnyE6WHAuzbtnE0yYeVXEqBKaN8YC26bHH/7v58rWzLuhbu5q559pzufvac/jUW87i7mvP4XPXnlucsOt5luSjt9MWe5Ux289xWolJfjZzlL+z7udc+SDgBHx+4ZeHnMIZluVsUDMbUVcAZGV8I7oaEmPORrSKVVfrqSDCdEVlYOJ9tK41UNgHWhacfAWOPuX8W0A/zHXOqdTnTf7sWimMVA6KFr+HDh3ijW98IwBut5tYLIYkSfzd3/0d9957b8kbmMtDDz3Erbfeyh133MELL7zAa1/7Wq6++mp6enryvv7IkSP88R//Ma997Wt54YUX+MhHPsLf/u3f8v3vf7+s7awWGSvhs4eH2NcfrmrloVJQTxNrsczWVzOJod8ddZ6b0++fdUEdhdggKNME4Khex1KcGJ36uQUuBLl5fvNRyYjiuVTIyrUgjSZ0Xukd45XeMPv6I7zSG2b3iVEMyy64/ZZl842njtI7mkTGcZ/QFBlVlvBrCsp4JblYyuDoUGzGBW7y74kknaj2S9e2cMNFK1na4OHMjoZsVgaAsaTzGw4NRjkxmuDTj+7jg995gbt37GcgkiLkVbFxFsNMRcTReJov/Oog4YSR9bGVsv85YiKpm6gyWLZTHW0ufXDdtpWospTdaDR6NZY1erFtsiWlLdtxbeho8rKqxY8iy1lxOxOKLBH0Fnb4WZQQmHwvmAY8dy9SYpRjdjsx2w2SQgIPx2gnSIxrrJ9nv+fwqZhT3XJwr3MyM9NGdGAv7PtxUQKsVEx2/6l21czZKKlQ7HkWHn4//OAv4ce3Ov8+/H7n8VkodVU+UeVvbhTt9tDc3Ewk4pSdXb58Obt37+ass85idHSUeDxe8gbmcvfdd/O+972Pm266CYB77rmHxx57jC9+8YvcddddU17/pS99iZUrV3LPPfcAsHnzZp5//nk++9nP8ra3va2sba009XL0lI/pKjKV06+ylhOcTxZDPreaLefq1xQShkXvaIL7njpa/O+fbUENtEL8FCSGINA+9f1GwnGR8DaefqxIn8Ry5vmdC8Ue8WUsSDu7hwkndEwLXKqMIssYpkU4aWDZEEkWZvndPxDhlT5nA+QeD07LIElOZbG0YeFzqaxs9jMQSc3ohzfd79k/EOG3h4dJGRZqTt7aQwNRYrojBl2qTMir8uyRIU5FHevxcCyNLEn43QormnyEPCqKJHEynKLB64zNTLaOTJvBSQXmuENILA3NnM1gpjZ/57nT+blHEzp946nlAh4Vw7RIGY7gOzYUZ2nIw+s3teFzyXx/5wlURca0rKxQhvHfqcjopsUrJ8KcsSwElGheyHcvBJbC8GGsQDtSTMe27Byrk8QpGllFLwfG22bZNmNxHUsaQU8miCvNaLaBf9K9gp6CkW74+T+DrFbcF7geCyIU4s+aGySdlxK4opTarWAxuCmUmqLF72tf+1p27NjBWWedxTve8Q4++MEP8stf/pIdO3bwhje8oRxtBJziGjt37uTDH/7whMe3b9/O008/nfc9zzzzDNu3b5/w2FVXXcXXvvY1dF1H06ZaZlKpFKlUKvt3OOz4Wuq6PvtNMU7mdYW+fr7sOjbCZx97lbGEQUvAhUfTSOomB/pG+cyjUf7hqo2c29lUkbYUy65jIzzw7DEO51RkWt3iY/3SAHtPjNDkUVGxkHIlgQTLghpHByPs7R1hQ/v0IinTB/t6R4imbfrGkvxm/yBHTsWz37em1c/12zorco0K6SufS+VA/xgaFn63jCJPtJyokkTasNjfPzbr759CdNjJ1aQ2kPfgx7sU1OMQC4O/Y6JAtm2IjsKys6BxHeg6HH8efvlJ5wg20HZ6IejfBzs+Dq//GKw4HzjdF6ZpcOO25Xz2sSh9IzGWBFzZiOKhaJoWn8oN25ZjmgZmfuNwWVi7xAtLvNk2zvTd77xgOc8dGsC2TIIuFVmysWwbC4tGt0zAI/PgM0c5e9nsC9BIJIFtGrhkC68qI02yWWqSjWTZuGWbD/xBFyGfRjih0+DVWNcaQJalvHPN5N+zusnDxjYf+/rCNLi8KJLzPYpt0eBWSBkWAY+KVwFdN9BkG1WyCbpVbMsmndY5fHIMRZKI6QaKBLFkGte494oi28jj96mNPZ5azKCjwcPlawsQFbO0OejyMjAWQ7Et/B4FbJsk0OJz0dnkoXcsxfoWL/92zRn8+OU+frLrBF4NFFnBsm1s2xnOsuSUKE7YgGWi6/q089DrNrSyLOSZcK2nZbp7YfAwJIbQ/O143F4Spo4kk53TEqgEZWedCbpkQh6FE8NRnth9krdENSLRCGnFg9+l0tHkJeTRIDkKQ0fBlsDbCt4l09535SIzbgMuDYWpFueAS2IsZjASSaCP92ktcHZHkH9/6xYODkbz3kczrt+WBc99HZJxaN6QExPhhuaQsxn53f+D9nMLiokoZs4phFJ/XrUpVksVo7kke7LzyywMDw+TTCbp6OjAsiw++9nP8r//+7+sW7eOj370ozQ1lUdA9Pb2snz5cp566ikuueSS7ON33nkn9913H6+++uqU92zYsIH3vOc9fOQjH8k+9vTTT3PppZfS29vLsmXLprzn4x//OJ/4xCemPP7AAw/g881QDkkgEAgEAoFAUBXi8TjXX389Y2NjNDTMfNowJ7eHDLIs86EPfYgPfehDxbdyjkw+XplceaeQ1+d7PMPtt9/Obbfdlv07HA7T2dnJ9u3bZ72YGXRdZ8eOHVx55ZV5rculZP/JCB95eDdBj4LfNbU7Y2mDSNLkzreeWbCFMJ8VpNTWUcuy+fDDL7O3L8zKJi+SJDGW1Dk0EEU3LCzAsCy8qmNTUGUneCcTpFPI79p1bIR7Ht/HO5aN8PDJJg4NpYgkdSRAU2TWtgUIeTRs26kEtXlZA3e99axprTvzvS6F9tVfXr6Gz//8ACfHkuPH6RPbY1o2acOiPeTh/77jnOIsv5YFP/pb6N8NTV1TLbsj3Y5l97wb4ff3w9CBHFeGDfCad5+2KA3sgx9/ENwN4PJP/a50DFJh+JP/gLZNee8Ly7LzWmDKRam+7/mjw3zyR3voaPSQ1C0My0KV5ezRtGnbnBhJ8LE/PYPzV83sdmRZNv/4/Zd48sApTMvC6zrt5mLbNknDCSh73fpWPv22s+d9fTLjeH/fKB9YG+WulzQ0TWN5yIsiS+zrDzt5cnUT3bIJuJygs2jKID3uvzmeWAFp/P8te6KPrQR4VJm/v2ojf37B/AOhdx0b4b9+eZDfd4+gyjKy7LgDLQ95s3NC5pq/9w9W09Ho4T9+sZ99fVFkCdyqgixLWJZNynCyRGxd1cgXrtvKRx7ZPe08ZEsQ9Gh0NXsZjuk0eNX8J2mT7oWxpE7vSIJY2sAyYYN9CD9xUi1nEba9HDkVx7RsJMlmBQMcUNZjnHUDD/U24nJp9I+lWNnkZU16H28Z+To+K8aY0kREV2nTonQa3UiKG9o2gqdxYlsm3Xfl4vc9w3z4+y9zKpJGkUGRZXxuheWNXhrcakFzai0y4/rd81v42YchtDK/ZdeyYKwH/ujTsPKiyjR4AVOslsqc1BdC0eL3iiuu4IYbbuDtb387oVCo2LfPmZaWFhRFob+/f8LjAwMDtLfn8U0Eli5dmvf1qqqyZMmSvO9xu9243VPzAGqaVrSQnct7iiWatonpFk0BDwZTJxhV1YjpOtG0XVBbdnYPc9fPDmTLPzYFPCR1k5d6I3T/7EDJHOj39Yd5dSBOo9+DKSnYwJHhJDEdvC4NLJu0YWAZTgWnmGFxZCTJFo9TTakvonNmR2jaylSWZfPNZ08wFHfOfQxbYTRpospOUEZMNzkynGRLhxtJgpDfw76BOEdGknn900pxXQrtqya/h/VLQxwfS5NMO76euWIoMe5HuWHp9L9/Ri58r+ObNnzACZrJHM9GBhxf3gv+wvFZW3XxzIn19TDoEfA3A8bU71FViEac1+WMvcn3xZYVpfFJn81ns5R+8U1BL5KiEtPB7z5d4StzyhhLG0iKSlPQW9B9d+Ola9hzMkb3UJxk0sStyEiSRNJwqrR1LfFxw6VrcLuLryY2mQvWtLF1VSs/230C/chOljcFCPk9SJLESDxNwpTwqjK2BGnLJGqAZkHMAMt2rqcsORvStDnx4FDC8ctvDbr5t7eexYVr8s+zc2nzP3rd/PW3X8CjygQ92nh6Myk78vojSU6E03zxN0ezRTZsSSFl2aTTTsU7CQlZVuho8vDXb9hE91hqxnnItGxGkybLbYVlTS66h+N869kTbF3VOvG+y7kXRhNxjpyMYpi2s3lVJYaNJhqMEfTBAzS1rSG0zEPf4Che/RQRAjzhu5I/AN5+QRdffepYtj0H3Fv4fuN7eX3kETrSPTTaaaSkgaJaKC2rwBNgyr03zX1XSnZ2D/Nvjx0kZUrYskzKAhWJeMxgOB6l0afR3uDhnZesLsmYrQZ51+9AMygSGGEnSHgyRtR5PtBctmu/GClUSxWjt4rO9nDWWWfxT//0TyxdupS3ve1tPPLII1MKXZQDl8vF1q1b2bFjx4THd+zYMcENIpeLL754yusff/xxzj///LKL0kqRG3mej2Ii5ysZvTs5XVQsZRBLmbhUx2tQGV9cZdkRAIokEU0ZnIqmCorMzQRjtAScidewLCzb+VwJcCmnS73CzOm1SnVdCu2rJr+L91y6io5GD5btCCndtJyIf91JIdXR6OXdl66am0Vl5TYnKGPZ2ZAcg9Fu59+Oc2D7v54O1pBlaN8Cqy51/p1s6fA2OhZhI5H/e/IFx5WJ2VLilTpzSKFpkwoN2tva1cxdbz2LC1Y14VJkErpFPO3ks71wlfNcKQNXZVniDRvbAKfwQwZNlpElxy3cAkJejZBHy94/GSSYInwhY/21uem1q0smfDNsam/gzOUhUqaVFb4ZRuJpDg5EMW2b1oCLFU0+ljZ4CHoUVEXC61YIelTaQ25ev6ktez0LmYcsG3TLmhLENYHxe8HWExwfTmCYNl6Xk6kDCSzFzYjSyhGpk/DIEKFUH5uaLJrWXoB81b/ynne8HYBlIe+UNICHPFv4asvtfLX1H7l/ya18xf0ukoFO597KR5nvu9z5cNPSIBvbG2jwqNg4p7CZNHO3X70AMw20bnaCCiMDzklZLrbtPN66yXldjbHQskHNl6Itv5///Oe55557+PnPf84DDzzAu9/9bhRF4e1vfzvvfOc7ueyyy8rRTgBuu+02brzxRs4//3wuvvhi7r33Xnp6erj55psBx2XhxIkT3H///QDcfPPN/Nd//Re33XYb73//+3nmmWf42te+xoMPPli2NlaaUia5rmT07uSE47ppYdk2yrjAMm1QFYmVzX6GYimiSYO0YTEYTbOmxc/bti7nvBlcDU4vao7oV3MWdVU6Xeo1M1HPtEko1XUppq9kWeKut56VLXqQ0C1s20ZTZTYtDXL7GzfNb2FZuc0pVDGfkqmZhaDvJacAxmQXisiAI6jLvBBkhG3GKu/R3BNKDd9+9Wa++VtnsW4JuEibFjaOhbJrjplDylEGdGtXM/e/d1t5ippM8xsAGrxqzm+QcasK4aSOR5VZ0xog5FEZjKTYPxAlZVhIOPcROCI4dwnVFEcwP3d4mOsuWImMXbKyvNNd84Rusv+kU5J2U3uQgMe5h3XTxrRwinuYNq0Nbrqa/dx40fRV/vLNQ7LkbApghnKx4/dC+vgLxFJNuNScHNa2Tcgc5qhnI58P3EZj4ij/eEk7XcuXE2rdTEiW0XWdg0xMA5hbiMGWZE641hCzDSKe9RhL9sHI3qrcd5Pnw0afRsjbQCxlolsWhmmhm3bBaeTqCll2smk8fodT8Cfvydn7a670dD1ngyoXc+ohWZbZvn073/jGNzh58iRf/vKXee6553j9619f6vZN4Nprr+Wee+7hk5/8JOeeey6/+c1vePTRR+nqckpn9vX1Tcj5u3r1ah599FGeeOIJzj33XP7lX/6Fz3/+8wsqzVkpcxdOtoJMplTFB2Cq5UxT5GwUtm3bpE0Lv1tlaYObLR0hloY8Wf/X/nCSrz55dMZiF5OtrH6X42ebNh0RmSltqinyrJa6Ul2XYvsqI4Y+9idncMayIK1BN80+jaRh8c1neuaf53g2y24h77/wA+ANOQtBOgqW6fw7fKQiC0EhVvkvPHGQF4+NMJZIs6cvks3H+0rvGGNJY3pr3ixs7Wrm9qs309nkoz+c5NBgtOj8mpOtMQBndIT4s/M7+bPzOzljWajs/pL/cNXGbI7QE6MJgh6VgFulwauhyRKW7bgeqXImk4NDvlZJSCwPeTgwEOXYS7+acy7U6ciX03QwmkKWYF2rn0afc9IzGtc5MBAhkjJwq071t5BH49hInLt+etrSX+g85Hc79/60m+TxeyGtNrDU6sdnJ5FsC7eVoM3oJS4H+WXwzbjcbvbbnfQ3bs17z2XSAM50orCuvYHga2+p2n2Xbz6UxlPPNflcNPvd6KZVknWiJin05KxGWMj58ufDvLZm/f39fOc73+Fb3/oWL730EhdccEGp2jUtt9xyC7fcckve577xjW9Meeyyyy7j97//fZlbVV1KVYu7HHXCp2OyFacl4MbnkgknDWRJQpUlVjT6sn6Ix0cSqIqzsHpd6gTLXj6hkVnUDvSNQrszOa9o8mXLvVq27RzV2Tb7B6J4NYXLNraU/boU21cvHBvhged6CCcNVjb7stbFmX57RcksBNncpgPOkWvHOc4CXIKFYCZf3kKs8nv7IgzHUiiShFtTUGQZ07KJJA0OnIywtjUwp03dzu5hvvnbbk6Gk9nNVFvQzQ0XryyoT2rFGnNuZxNbV7VOuMaRhME3fztxjG5sD/Jy7xiGaectIiEznqcWiXWp3TT/70NgR0telndyTtOe4ThfeuIgrUEnl7Bt2xwfiWNYNl5VhvHgPVWR6Gr2TbH0FzoPzXqStnIbw3/wMQ7/5HOsso4Tskcw0Ohxr+eXwTdzyLOFZMqYca4o+EShq7ns9910VHKdqAST55fVTTPnpAZKc3JWASYbB0qZL7/eKVr8hsNhvv/97/PAAw/wxBNPsGbNGq6//nq+853vsG7dunK0UVAApUhyXa464TO1OVcIaorjZydL0NnkJehRiaaMvEeas928mUXkM486742lDYIejc4mL0eH40i248u3rz+S/X1fffIoT7x6aor4KPV1KbSv6mbiKuNCMJtAPG2Fyu//6NYUwgkdy7bxudSs9VKVJRTZOTLvGY7R3uAtarGe7GrR3uAEQB4biXPXo/tm3ZTM5qpR6U1NpoJZLlu7Jo7R0ZjO339v13jluIlBVqoi4VMVDNsmkUzzFv1RXEYYWtfl5EINOMf0w0ecsrwrLpiXC0SmvSGfhltTs2IsljKJjftLS5JTHS9zypPPTamQeSiWMgpyZ+k8+wru3hMidvxl1gUN4kqQXm0VtiRPmStyRVfAdfrzCt4gV0mAVXqdKCf55peNbT4uLySraebkrIapx0IklaJo8dve3k5TUxP/f/buPD6usl78+Oec2ZdkkjRN2jRp2tKVslppKS6AQkGQzQWwWhCvCyoi4lp77wX14nYRVJQrclUQQdELchW9LAqK/oACpezdl7Rp2ibNMvt2znl+f0wmzZ6ZZCaZJN/368X1dtZn5sk5832e8zzf76WXXso3v/nNcZntFbkZ7Acs3+cXeh3jSPoHgge6Yjy5tY1dbVGaO2NYMOCSZtZIB++Kxiq+cM4SWl59hnDCJJpO47TbeOeSGhqrvTzy2mHiaZM5FR48w8yoFuN7yaWvJtWJq9cPQaEq6OUSII40C9UZTWEqhc+VWfJi0/Se71IDHLpGOGFyQr0r5x/rsQxKLEux9XCIWx7LlA5eVOPvqYxWaoOa/n+jWw+FCHiczKnwsLM1QiRp9JRhzlRSU+iWYkZiD4v0FpyB2UOX5W3bmgnaRggecvlb6h+MpXttblVAyrQoc9t7/j4GW7c70nko1ytpuq5xxVvmc9OfEjweS2fOFUojkeobPG/e39kn6PI5dD7SmEnpdsqCmtwnMyYgANN1jXWr5/LvD73O1kNhqv1OKr1OkoZVtN+JYhjq/LL1YIgzjjnaF5PZSJMDQ65hnwbyDn7/93//l7POOgu9xKb3RWEUaglFPvr+yM7g4pPqh7yk2d9IB+9JDZW0vArffM9xRFKKgNfBwmo/1//uZUxLsbjGn1PwMtL3cnJDJVsPhQpaWnIynriGm6k9oS73maBcA8zvvf/EYWehjkSSOGwa82f42H0kStywcNp0bN2bH1OmQtPgzCU1OffXaAcl2e/mtQNBmjtj2HWdN8wQ9ZVeKrpz1ZbcoKaXniDzQJDachfJDgtTKRzds5oJw8SuazS4k8xAoTmGqOpl92Qu08e7hn2/XJeF9B+cZnItZ/rWVFZm6UKlt2eN8lCX5Yc7D+VzTI90rgAGBF2GkTmGb350G186z86KxqoxT2YUy6amDu55Zh/xtEkoYdAezZTBrva7OLG+omi/E4U03Pml3OkBQvx64/6BKe0mmam2RKWQ8g5++5cLFlPPRNcJH+6SZn+5HryLa8t60tttPRQaVfByckMlnjNsvH6geyd+XTlLZ5WzeX8n193/UsHXbk6GE1fvmbn9nTH++6nd3ZvInMys8JA0rKNZF85dlPPr5hpg7jwSGX5W3uvAaddxO2wsqimjuTNGNGWQ6t7F73VmUmCtXJB7P41mUNJ7lslt17HrOg6b1rPueFGtH7uukzYzaf2SBdpYWki6rrFqQRX/2NFGNGkCmY2jaSOTBsxh0zm5oZK1K8rxbPRm1vgOmgt15FRc+S4L6R1w7jgcRgOShkWF105Dla9ncJHPZfmxBJ9DnUMBrrv/pQFBl6u76E0obpTErP9QevfLrHI3jTN8dEZTHIkk8ThsfOjU0g98YejziwKi3Zuk3zgYYuuhEMfWjU89g0JdMettKi1RKbQpmItEFEKpzDoU4+AdbfAy2CzUqgVVPLCpuShrN0v9xNX7OwnGU7SGkhhWJrF/OJHG50xSX+nt2WT06437OT3HCuH59NGqBTOGnGn70KmN3PNsE6+3BGms8vZJyWTXNY5Ekhw/pyKv7zDfQUn/WaZo0kTXM0G8x6ETTRq8fiCE3aZjqUypNLtN40BXDChsrtyx2NTUwQObmvE4bOiaRsIw0S2FaSpcDp2r3jKfz521OJPebNfoU+CNNOu/tz3Kj/66k0+cfgwVvqNBQu+A87ndHfz6uX2kDAuHnsneUMzlW4MZ7Bw63MAbYIbfWZKz/jB0v8wsc1Ht7y4A8mwTKxpLM3DvbbDzS1c8ndkomTagFg50xrnpT1u4fs3iogf0xdr8OhFLGScLCX5FSSvGwZtv8DLULNRrB7r4x442vM7MTvhCb0gr5RNX7+/E47TRFUuRtlQml7Jl4dBthJMGO1rDLKopY6bfxa62KKc35vb6+fbRcFcrdJ0+36HHaUNLQ1skSYXXmfd3mO+gpP8sk8+VSbsXThrYLS2zRtUCh13HbdOJpTPld+95ponGGb5xmUkbadapf2EDYMAgYl97LPPgMeZCHW7WPxg3CMYNnt7dzs62CGVuR58gIRtwLp1VzvI55Xkv3yrG7Fuf9ucwqEuF0yU36w+TbA/CCPqfX7riaXYcDmOYijLn0U2xTR2xom9ALfbm14lYyjgZSPArSl6hD958gpfhZqGqlYvmzji6xoCNPYX6MSilE1c2MOiKpvnJ33fRGU0xr9rHGwdDGFZmGYGuZSb30qaFz2kjYSqau2IsrS0jGB28st1gRjPrPdTVikJ/h/kOSvoHPL3T7kVTJpZ19PtNWAqnTWdRjZ+u7sqBxb4E/tL+Tu7ZeGDYWafBAh+/++jPh65pff/Wx5ACb6gAMZu7N929TnuG34nbbht2KUQ+y7fGI/XcZFjKNJTJuAdhKL3PLx6nLTPj212VT9cyB6TfY2fhTB/7OuNFOw77/76gaUSTmYqeM3xO2iOpgrz3RC9lLEU5Bb9VVVVs376d6upqPvKRj/CDH/yAsrLpt0ZETJxCHrz5BC/DXaY0LJUpv5y2iCYN/P1+zAr1Y1AKJ67egUE4kaY1nMTvsnM4lOgpB2t0l8vUNIVhKSyyZaQNOmOpvlWvRlDoWe9Cf4f5BNSDBTwVXgf1FR62tYbRugcMSkGZx059hZcKrwOHTR+XmbSbH91GW9QcdtZpVIHPKFNxDfZ99c7d67RpmErDZbfllPIwl+9uvFLPDTeoA2iPpFg8O79lOONlMgfu/fU+v+xsjRCOGzhs3ctjVCb4nRPwoOt6UWe0ew8qg91FW6JJE0tl0vO57BovN3fl/d5DXcEo9Rn58ZRT8JtKpQiFQlRXV3P33Xfzne98R4JfMe4KefDmGrwM96Pv0DMV50xLkTJMIgrSloVD1/G5bKP+MSi1E1f/wMBp12iLJImlTPa2xzAt1V1ZLVPaVO9OMaUU2HVIKTgSSXHqvAqgM+f3LcaMbSG/w1wD6qECHrfThrN7na/XaWdRTRl+V6/7izyTZnUPVoJxg3kzfMMu2xl14DOKVFyDfV+9c/f2T1021qss45lPe6hBXdLI5E0u99hLdg1mqe9ByFf2/HLLY9s5HEoAOrquqPTYgRQBjwOD4h6H2d+XpKmzqzWCYaruSqaZ1IGxlEk0afLcno6c/65LpXhOqcsp+F29ejUXX3wxK1asQCnFtddei8czeBqbn//85wVtoBDFkkvwMtyPvs9lw223EYynaeqIkTIy+UV1DXxOO3abxpsbq/L6MSi1E9dggYEC7HomXVjStDAshWlaeBw2olYmA4CmAd3ppgzTIuBx8IFVDbS82pzX+5fCrPdw+gfU2XLF/ds6WMBjmBamlSmpu2CmnzJ337+vYs+k7WzLFICp9jtHXMM5noHPYN9X0jAzf2eWicOm90ldBmMLUMZ7LetggzqfIzMb/oVzlpRsgFLKexBGa0VjFRvevYxr7t2M265T5nYQcGlArOcxxTwOs78v+9qjPcsust+eXdfAbiOWMnhySysfWjXyd1voKxjFXgM/kXIKfn/1q19x6623smvXLjRNIxgMkkgkit02IYpupNnAkS5TahooMqVy3XYbbrtG2lR0xFI4bDorF1TlfLIotapfMHhg4HPZ8blsPZ/ZMA2ShtUzUxZNZdb2JtMmltKYWebi6xcv56Q55bS8mn8bJsvlupEGLv0DHodNZ2ZZ5opCoF/gOx4zaaF4JlB0O2wDShVnb88GlOMd+KxorGL9u5bx4yd3src9SjxtolRmwDmv2t+TuixrLAHKRKxl7T+o8zs1dm76Byc1VBbsPYqhmHsQJirQWlpbznFzArzeEmSWy4amHT0ain0cLq4po6bMxc7WCB6H3mdAp5Tqvsrh4FAoMeLgq9BXMPovdbPpGvNm+Pj0mQs5ZX5pDtDykVPwW1tby7e//W0A5s+fzz333MOMGaWTgkeIYjpjSTVbDobY3hphTsCNx5nJO9waTmBaikqvE12DWMoiYVjomkZl95rN53Z38IFT5o54ssmeuILRJG8pb8OvIkQNPy3OeXi7U4VNRP7PAZu1lMWc9F7m+Lp4I6WzxahD13U0LVNCGjK5c2v8LuJpk4DXwdcvPI5T5lWRTpf+RpjRynXg0n8WOxw3+Nb/TcxMWrnHQSuZwNHlHLgee7CMGuO1+XJTUwf3PNvE4VCCtGFiGBYOm4aloMzVt61jDVCGurqjlCKaNAkn0pn39cj+cCjO1ZiJvOLVf2A3uyzz9x5NGRwMp4t6HOq6xjuW1vDM7vbugjuqVwGeTCaVuVVewomRM4AU8gpG9nx2OJQgkTZJpDMFbVq6Erzc3MUXzlnCB1flmLqnROV9NO/Zs6cY7RCi5PQ+IcdSBuGEQSiepsxtJ+Bx0ljlw1JRZpW78brsPbt0HTYdn8tOLGnkfLLZ3hrG0fI8XzP/xNwj+7GTxsBBi3MuT5RdTMy/ZELSCPUODE5Q23hH+CHqUvuwkyZpt7OV2dxtrGG3ezmJdGajSJnbjsth47g50yOVTr4zLv37b6KyeSyc6WcnmU1WsysdOS1lKEbg03/GL5xI860/b6Urls5U6YumSRlW9+y0yT92HKFhhpd5Vb6CDBQGu7rTFUv3FERJGpklPf/15C4+/JZ5BemT/sFe//LGpa6QV2NK4YpX74FdU1sYgHDCHJfjcOWCKmYH3IQTBknD7CnAU+bObH512DSSOVzVKNQVjOz57HAoQSiexrTIFArSNQzTIpI0uPnRbSyu9XPKvMk7CTqqoezf//53br75ZrZs2YKmaSxbtowvfvGLvO1tbyt0+4SYEP1PyDVlmZnMlq44boeNj75tPnUBD//60Ku4HZl1WmPJ9mDufZaPRP+bSj1G0FZFSnPhVEnmJndyafonWJWf4G/G/HFPI5QNDNT+Z7nUuBuvFcm0DydlVpCT2c5ydwvBM7+Fbd5poEE4bpTk+rBiXVYd64xLoQLKfD9f9r5yjz2vmedCBz79Z/yC8VQm84Xbzs7WaM86eg0wVGZWrOlIjGjCYGaZe8wBSv+ZP7ddZ39nnJSZGcy57ToNVV7eOBgqSDA2WLA3WHnj6WA8NxuOJHscbmnpZOemf/DN9xzHsrriv+/imjJOqK/gtQNdVPt9GJbq2TQN0NQRy+mqRqGycWTPZ4m0iWnRZx2yw6bj607HdvsTu/jZh3Nf1ldq8g5+f/WrX3HVVVfxnve8h2uvvRalFE8//TTvfOc7ueuuu1i7dm0x2inEuBnqhOx32VlU46epI8bft7XxidMXFCb1j2VRv/NXBIlyUK/D1p0KKql5aNXqqDFaOCP4vzzj/ty4pxHSdY0rVzcQ3XsDDiPEQfscylSUeqMZlxXDhsJlBZm78Ysw505oXN3nc3H4jaNprioWjmvbeyvmZdVSyH86ls/3hXOW9OT5Hc+Z58GCwI5oirZwCoctk1HEUmDTQOv+gbUrMLuLqSjgP997Asvqysf8A5yd+bvr/+3l79vbiKdNnDYdv9tOfaWXCo8DpVSfYAzIe8Ay1LllspQ3LrRSK5yh6xqLa8vYCSyuHZ/B+9HBV4z2aKpnEBpL5XdVo1CbUoOxNOFEmkTawmnvuw4ZMsejrmvsPhKdFAVNhpJ38HvTTTfx3e9+l8997nM9t332s5/llltu4Rvf+IYEv2LSy/WEjEZhdsC3baE8vJvDrmpSKYWn95JGTSNoq6I2tZe3zToyIWmEVngOE/O10RyfiTsVYpa5Hwcmpu7E7rCjY0CkFf78BTj/lkx+130bexU4SGYKHFQvB8d5Q2ZEKJZiX1Yd64zLWAPzsX6+kxoqWTFv5rhuNhoqCLTbNGw6pE1F2lToHA18IbPBVNPAZdcJJwz2dcVYXh8oSJtWNFbhcdh4/WCoZ+e/z2Xv+fHvfew/9NIB/ratLe8+G+7cAqVd3rgYSmHgWAoKsZ6+UJtSA15HJoWnUrgHeaypwKZrWEpN6n7JO/jdvXs3F1xwwYDbL7zwQr761a8WpFFCTKRcT8jhuFGYHfDxLjQzSc2M2QRb48RTmaIRNi1zAgql7dRpBpcs8+YUkBT88n68C69usGj2bIxDr6GlFNh9uG3dswJKB9PIzPA+fycoCx7/t8y/y2qPlrY99Bo0nMd/3Xc/j4Xm9Q0aVjewwnM4r2IIuRiPy6oLq/3UlLnYfjhMfaUHv8ve8z4jDYJGClzXn7eUMrcjp7LDY/l8451RY6gg0GHL5Di1VCZjSP8WK5UJQu02nXTa5FCwsFmHwgkDHagpc2Mb5PtyO2zs74zxX3/bhWmpvAcbk7m8cTFMpcIZY1WI5U+FCKIX15Qxb4aPlq4ERvcelqxsBgqPw4bfZZ/U/ZJ38NvQ0MBf//pXFi7sewnzr3/9Kw0NDQVrmBATJZ8T8tJZ5WPfsOSpALuLCrvJolo/zR1xoimDlJWJ/ypdJjM8ZTTMmzviSxXl8n53+7REBw4zBg5X38BUmWCzgX8mtG6Bf3wvE8RWLTha9tnpJ+jxArC85fdsnPF5XGWZoEHtf5bo3huI+drw6kb3LPESWPnxYcvg5qLYl1Wz3/fe9igd0RRHIknK3A7mVnlx2fVhB0EjBa7bDoe57jcvEfA48yo7XMjPVyxDBYHZNHod3aWw+6dgs5TCbtNRKlNSeVbAXdB2jXTsx7s3vmqaxuIaf96DDQn2+ppqhTPGqhCD0LEG0bqu8ekzF/JycxeRpIFP0wZkoHA7dBbXlk3qfsk7+P385z/Ptddey0svvcRpp52Gpmn885//5K677uIHP/hBMdooxLjK94Q85hH7zGWZYO/gK1RUzSdQ5yCaMjOZI3QNX3QfWt1JmccNo2iX97Pt2/dsZh2vrV9aLCMF7nLwzID2HZCOQXnd0cCXzPfW0pWAajhGb2GR3swBfQEnqG1catyNwwjRHJ/Joro6NDMBB1+BxzbAmpvGFAAX87Jq7+97VrmbSp+Tfe1RwgmDNw6GmB1wc2J9xZCDoP6Baza1VtqySKQsumIp0ibM8LmoqfQOOiP8zK52wok0M/3Ogn++YhoqCNSA+kovkYRB2jSxAN1SoGlHS77aNBJGphzz2UtrC9qukY79A90zzXMqPKMabEzm8sbFMBULZ5SCsQbRp8yv4gvnLOHmR7cRTRrouoZN1/A4bLgdOrXl7knfL3kHv5/85CeZNWsW3/ve9/jtb38LwLJly7j//vu56KKLCt5AIcbbaE7I2ZNNdsnB83s7cg+CdT0zy/nYBujYg1ZWg9/hAS0F4VbwVMIpHxt2GUBRL+9n29e2BaJtYKbA5szM+BopsDmgYi6YCdBtmQDZ3rcCZDRl9uQBdmDgsyJoyuId4YfwWhEO2udgGIqoAX6XH6p80LEns4yi/pQRl0AMtdRjzDNtlpX53P2WYwz2ffuASq+TSCJNc2ec+dU+vvf+E7HbB29778C8d2otS5FJ7aUUNl3rXgerDTojHE6kaQ1nSk3Pm+Gjwlu44g/Dff6xGi4IDLjtVHgd2G06wXgaQ4GmFHY9sywiYVg4bTqfOnPhkN/taI107HscNpRSeBwD8yLDyIONyVzeuFjGM3+0yN0HVzWyuNbPj5/YxZ4jUSyl8LvsLK4tmxL9MqpUZ5dccgmXXHJJodsiRMkYzQl5TEsO5q7KzHL2bBJrzVz+rzsxE/iOMPtZ9Mvfc1fBed+DBz+W2dxmGmCzodzlxL1zSFpevOF9OKuPQQsfyqzxdfp7np42LaxM5igM7ER1P3XpvdSl9hG0VWHTdFLpzGx3d6OhrAbatmaCr9rlQzZtuO/95IbK0V9WHXTTXmY5xnbnskG/bw26lz1oHA4l2XkkMuT3nQ3M28IJ9nfGMSyF06ajlCKhMhf8DUuRSJs9zwnGDYLxNClDMcPnYsFMP7GUQSiRZkdrmEU1ZT0B8JgvGw/z+ce6HKV/EFjtc2IqiCUNQkmDmjIX37/sWJ7a0cavN+4jlEijAFNl1tl+6syFfZPsWxYcfh0OvZz59+wToWY5FlreV2SGqsY3t9LLsXPK+L9XDxNPGfjdAwcUuQw2Jmt542Iq9TLm09Up82bw8w9XTcl+kZI1QgwhnxNyQZYczF2VmeUcxUzbuOyablwN77kzk9Uh3kXUUcneuAejPUaFdYiDmp9Hyy7gCu/jzAhty8zedgeGDptO9ms76JxLi2Mei5KvYSdNSnNhKoXePbPXw+7JDALiXUM2KZfvfTSXVa2mZ0n8eT1avAvLX4s3UNtnOYZ53JdIGc4xfd+La8o4ZqaPJ7a1ohR47DqappEyM4GvUpkgsT2aYlZ5Zm1rc2cM0wKbnsmMYNc15lX72X4oRDxtsrc9ynGucpKGNbbLxvs2Zq5E9N60mI7B/ufh8Gvwls/BCZeOaRY4GwTe+vgOXmnu6g7yM+sJ583wouvw+TVL+Ow7FvH4loMkD7zOLFeCNy+pxz6r1/6SfRvhb9+Clhch3b0BzuEmWHkcP3d8gMfD8/IejPY+9p/b3cETW1s5HE6y77UYRyJJDocTLK0to8J7dLmJpRQHuuLMrfJiKYVlqSG/98la3riYhrpUP1Flj0XGZCkvny8JfoUYRi4HfkGXHOj6sLOcQxm3jTSNq+H8W2h/8jaC+17Hb3Vi2Zy0uBfzf5538/+6Gmm1n84GezP+jj2Z2Vu7Bx9xGvQ2WoG/+96F0nSiuh8DB06VJGY4KXPb8fUus2vEM7ONnopBm5Lr937rZSflNYu/ae8R1APfpSbaygFmoccNfM4o9VUeKqrmQ8ce6nfei8v2kTF937qucebSmfxly+HuWc1MDk1FNqsBuGw6oXiatnASj9NGNGVg1zUUWs9AocLjYPGscvYeiRBJGuw+EqXM7Rj9ZWPLysz49t60GO+Ern2QjEA4AY98GXY8Bqs+0WcWeDSBSjRpUO5xUF/pwee0o+saB4OJo4NGbQfv2tZrBnpbrxlogD9+FtW5B0uBpbvRNA0tncB98Hku0vbTWXUd+yqPz3swquuZZP4PvXSgz+DK7bCxszXCay0hFs70MbPMTVskSVN7DNNSWErxhd++MmKg3fvckk6n2Zl7D00bE1n2WExtEvyKgpqOo/RS2HE/nrumrfqVfN3xOSLOV1lUbhCzldHimIfSdBqV4rmORdxZ9i9cV/Y3tPbMEg7N7sJRdzwAT8XmEdAM9tsb2WdroCG1k4htNvVVvTYRKZVZ71x34pAb/fL53nOdxd/U1ME9f3iET0d3E7JV4bHZMZUinDDYcTjColo/FWU1lId38daKI/ylfcaYvu85FV6qfE7SpkUsZZEyLTQUNh1MC+JpEwXsbIvgttswTIWmKco9jj5Bd4XHwXFzKtjdFuEjb53P6mNmDPr5eh+ffucQx2XblkygWVZ7NPBt2wZmGuxO0H2Z///AC/DYvp5NifkGKtnBSzCe7pM5AcDXPXh56q9/4k3m3WiJrr5p8w6+Ao9uAKcPo2sfpqGIaW6UCZqmUMqJmySzOMJ58T/y3/7j8h6MDjW4mlXuxmXX2X44wv7OOJ2xFJ2xNLqusaDay8wy97iX552KSqHssZi6JPgVBTNdR+mDLTlQZGa00qaFTdNIGmZRd9yP567p7a1hdrTFKK9Ywo5+s57ZoPPx8Dze9a7vsVQ/0LOEo6piITzyCEtnl7OtNcYRw+T3jvO5hl9wnKsDj80Fli0T3IRbMzO+g230696EZe3Zx5zkYQz/0kHb2X/pwUiz+NlgR48H8ekmMZsbNLBpGh6njXjKpLkjTmCWD81s5T3LvDy/yTHmhPIBT2bWG6AzluJQMIFpWX3SfGloRNMGaUPhdujUV3oH5MBNpk3K3A5WHzNj0M/Z//j0OXQ+0ggv7e/klAU1Rx8Y7+pe4+vJDEK69mWCXYcnEwwrhTLTdGkVaB1tRB//IQfO+D7ffnR7ToFKNgB/tTnIay1BZg4xeKnxOTjp4G9J+TpwzVzYJ20eVT5o24px+AgpwyCNE03T0LXM8gNLQRI7bkwaUzuoS+/lgHNBXoPR4QZXlV4ny+vKaQsnKXfb0TWdRTU+9O6/1YkozzuVlFLZYzE1jTn4jUQiWJZFefnUWxMicjedR+n9lxx0xbt37idNLKVAZdZnHuiKATOK1o7x2jWd8/riuAkLei3hSGeC0G+/53j2dCa6Z2DfRGPyBPTn78xto1+vTVjHJOJ8JWFxsG0uT1Vcwi533+Ui+S71yAY7y32VGMHMcoykdjRrhdOuE00ZxOJRfHYXS+bNZcOs2WNOKJ+dsa/wODgUTBBNZTa4ZQK5zOMy5Xa1nh/6cnffU/doimkYRqY/bn50G186z360vd15nTHimeA3FcnM+HYHIIl0GiNtsaM9hYWX8sirfOMXD7DPsYAltX683VXRBgtUNu/v7Pm+grEUbZEUkUSahiofFZ6+/XQMzTSY+0m4anD1r4amaShXOXQdQEMD3Xa0EhsaoDDRURg4VAqfFel5aq7r30f6O/c4bKRNi85YmvpKT0/ge7SJpZtnudSVwtU0MbWNOvh94403uOKKK3jxxRfRNI1jjz2Wu+66ixUrVhSyfWISmO6j9N4BTMq02NkawTAVTruOrmnE0iaWgnueaaJxhq+og4CTGyrxnG7j9ZYQAMvnlLO0tryg3/tY1xcPnIE9FRpWYh1+g/0HWwgqH8665SyuDdAnnOi3Ccvpq8VMHqEhuZNLO37Cb6uu7gmAR7PUIxvsHPEvoCU+l7nJnbRqR/MV27o3o2mRVmh8E8xcxgpdH3NC+StPa+Q/Hn6DrYfDGKZCdW+UUkph1zVcdg3DAr/LTk2Zi73tMXa2RphT4clt894Qx6fLmem7UNzoe3z2yjuNJ9Ant3M8ZWKlEkTwEtc8aFg4VRceM0LQSPNKcydvch/imDIDzVNBi2Ner5LAzfzq2X09AbjXaaMzliaUMNhxOMyi2rI+AbA9FcSJgc3lHfS7i2tuHICOho6Flf1r6f74NiyUggROovrRzCO5Dopy+Tu36RqmpXCPMvWZGJyUPRbFNurg9xOf+ATXXHMNl156KalUiltvvZUrrriC119/vZDtE5PAdB+lHw1gtrD9cATDtPA6bViKnpyki2r8dMXTRR0EjNeyk2KsL960v4u7n06zs9VDykjjtL/at+2DbMLSgJrqKnYcclBjHOTtXQ+xY+ZS4obKe6mHZSk6YikMS9EeM/hr2cVclv4JNUYLQVsVKc2FzUwwhw7w1PZZjjHW3dArGqtYt7qRG//wBgaZ5Q4amUpmHrsNh03DsBRJIxOEVfkyFeQ6Y+kBs80nN1Sy9VCoTyA+3PEJMMPv7Ht89s47HW7t/oIMlKah0nEM7BzSMssknFaKJA6C+HiTtp0reYxF6RZcnWn0sIvDrkb+4r+IJ435PLDpQJ8AXClFmdtOuHt5UHNnjIAnkJm3VYrmhBPd4cKnpYGBQVDa0jBxYcfEYSVJ6plZeo3MeMWpDCw0dtuOocUxD8jv7zOXv/P51T4OBRNSsa3ApBKeKLac89RcdNFFHDhwoOffbW1tXHjhhXi9XioqKjjvvPM4fPhwURopStvRUfrQsx+pIq95nWjZAEbXMmVXE4aFYVmUue3duVedfQYBhZa9rP3agSDlbjv1lV7K3faeZSebmjpyfi3LUmw9FGLj7na2HgphWarP/dlgP+DJrHeNJg0s06QqsoPy1uc53tHMFasbcg7wc2p7/01Y3So8ThbNKiPpqmZ2qgl7+1ZCCYPjZ5fxjdUaK9SWTP7XbJLhId7/uvtf4od/2cGRSJKth8L8b/scfu77KPtcC/FZEWYah3CZYVp9S3Cf980x57ntb06Fl5llLhbW+HE7dLxOO2UuOw5bdtY5swQiljQIeJxsePcybrnsRG665HhuuexEbr3sJACuu/8lrr//ZTb8/lWuv/9lrrv/JZ7b3ZH/8ZnNO13/ZrDZIR3FSKUIKQ+7qCeEH9NSVNPFTjUHPzE2OO5lub6XMF6a1UzaDQ9zkzu5tOMOjjW3cDCY6BOAa5pGfaW3O3sFhOMG4XiaaNKgqSNGp+8YPHXLMjPtql+hY6Vwp9rZbl9Mm60GDYXbiqErE12Z+Ehiw6JFVfOw+90YSut53VwHRYP9nZuW6vM6nzpjIYtqy2iLJFH92pgNkBfV+KdNxbZCyQ485HsVxZLzzO8HP/hBzjzzTK655ho+85nPcM0117B8+XJOP/100uk0TzzxBJ///OeL2VZRomSUnjGnwsNMv5NKnwtLKRy6js91dMaoWJfqCrnsJNfZ497rix0tz3Ne/I/Ms5rx2U3K8eF94UnQRy6GkHPbT42iZzdh9VPhcRKoqybVHuFzq2rxedLM3XE72saRizMMXAtbxo7WMJ2xNP+brGdrzedZ4NlPItRO0lXOu844kzc1NAxow1gFvA5cdht+l51yj4NwwoBesaqpMmuAQ0mDFXMrByxlGW7N/Y7D4Z5iGXkdn9m806/+Fv55K4lwmL3pcgzdjZs4VXQRwse91llcYfsLAaLsVTXYtUy+4ojSOajPoto4yOX2R7lBLR4QgFd4HSyqKWN/Z4yuWIqWYJyAx9kzkz1D+0xP5cNs2rzshkinv4qnyq9k95EInzB/y/zUdlwqk+c3pbl4XTuGnzsuY79tGanO2KjWv+eyjl7XkfK8BSZlj0Wx5Rz8XnrppaxZs4Yvf/nLrFq1ijvuuIPHHnuMv/3tb5imyVe+8hVOOeWUYrZVlKjxTLNVygJeBy6HHbuu4XONrvrTaBRq2Um+mxZXNFZxMttJ/PnXaFp3MQiPr08xiGwarLG2vSnmZH52E1avynE9jzUTuNwejvUG4fn/7lucIZsaq3d7LAvr8Bv88y8vUBmGyplLQbfhc8GS2nKaO2N0xlJsORxhp20GMIMy3c6Bfzbxt+3tRV1KMqfCw87WSPcmt0xxkIRhYtc1ZvqdA370RxxAtMdImxat4QTznL4B33N7JMXi2RWDH5+6DideDpXzCT/+A8r3vYZLhUhrDl5X8/iVtYYYHhbqB2hVATILNjKXFC0gbihCtkqWOw6ymBY60gsHBOAVXgd23Uuby84nzziG4+sDvdZND1L50OaCqnloi9awxnEM//60yXXxJbzJ38JitYeUYbE53UCHfxFfOf9YytyOMaVeHClNnpTnLQ75XkUx5bXmt6KigjvuuIN//vOfXHnllZx99tl84xvfwOsdfEOCmB5klJ4xUYOAQmwOGdXssWWhP38nXiMMtYuOLkewdaei6tgDz9+ZmT0cohJYrm1vdS9gfnYTVq/KccDRnMCzT4Dtj/UtzgBHU2Nl26MseP6/SR3cwiWdIS7UHRxub+SJsovZ5V5OhddBwFNOU3uU/Z0Jyj025lV58TjtRctg0vsYCsbTNFR5aQsniCRM0paFvXtj3XVnLxrwniMOIMpcHAolcNltfY7PpGEAUO6xj3h8WvUr6VzzY75+1wPoiS6S9nJeMWaDprNS34qLNAmcmfW2ZMoQK5XZpNdQ5SOQPMgSj8kfupKDHhtHoimOnxPgvW+qH9iO3pUPm55GbXuUZHsz6vB/cYzDzU/LF/BLzzk8Hp7Hi0Y9TruNRbP9XD1MgJRvPvKR1nVLed7ikO9VFEtewW9nZye7d+/m+OOPZ9OmTdx0002cfPLJ3HLLLZx//vnFauO0MZkLRMgofeIGAYVYdjKq2eMh1uF2Pylzmbpta+ZxQ1Sty7ntPtfRTViDXALHUwELz4ZnfzR8ew5sgtYtYCRJ2qtowU1ANzJrU9N9M0aEkyYKRV3Ajd+d+e4KkcFkqOO8/zFU5nbgdzuYXe7mvSvqufikOYO+Vy4DCLuu8YFVc3lhb2fP8elzZAYkXzhnybDHZ++lMG1aI0fM2WBmlmEoBZ2Wl6TuwEMK5fCh6xpp06LM5eCE+gB6Ogqmi7PetJi/P6NGd2zoOiQjRJ6/l2iwnUNWOXGrAo+epDb8Mh8NNPOe0/+dQ+UnjnjuLNbG0KlaBnaiTYfvdTL/9k9WOQe/999/P1dddRXl5eUkEgl++ctfcuONN3L55ZfziU98grvvvpvbbruN2traYrZ3yhrphDwZDg4ZpU/MIKAQM86jmj3uXQxhMHZP5jJ1vKswbdcHuQTeOyewZQzfHpsbIm3gDkDtcmwpE80WJKa5SdrrqDFaeEf4f9ntWkYkaRFJGDh0Hae97zrVsWQwGek4H80xlOsAYuX8Kj60qrFPhbedm/7BSQ2Vw7a391KYmrIATe1R9nXGMbs3Qm5T9exSc1iu72Wf6UYZGpoGFopQPEVFPFOpb/mJp7Khqmt0x4Zl0f7kbcQ72tivZuF02HDbNQxlZ0/aTX3HIfyv/IJVH7p7yKsMg32e6ZSPXJSm6VocaqLlHPx++ctf5uc//zmXX345mzZt4iMf+QgXXnghS5cu5e9//zs//elPWb16Nbt37y5me6ekkU7I711Rz8bdHZPi4JgOo/SRjPcgYCwzztlB1b6OWGaNZtrEn+vsce9iCIOsw8WIZ+73VBSu7b0vgXdXjmPmskzAc/j14dsTbwcrDf6ZoGn4nDZ8TjvhhIHHaSNoq6Iu1URdei+vmnNIWxaVXsegAeVoNi/mGnjlewwNNoDQlEVdei9eM8zOsJ1Z9cf3/A1mXzudTrNzmNcdbClMVzxNLG3itmskjEwWCqfdwb3mOXxZ/Yq52mE69UosuxstFSV88AD2qhr83anhRntsWIffIN6yhTZVgadXf9g0DY/LzpFkBTMPvIF1+A302cfl/Hlg+uQjF6VHBmMTJ+fgNxwOs2TJEgCOOeYYYrFYn/s//vGPc/HFFxe0cdPBSCfkbYfD3PzoNiq9Tjk4JpHxHgSMZsa594xDMm1wJJKiNZRkca2fSq+z53FDzh73LoYw1DrcuhMzjxtF25fXBThjyUwMM5N6rSdI0vXBl1GM1J5IG9gc4MlU2dM0jfoqDzsORzLFG2xOylUaPRGkLT4zs8GszD2gjDDkv3mxmIFX/wHEW5y7eFf8j8xKNaFbKUzNSSC9HL35M3mlaOu/FKYrns5kjjAVTrsNhw1ShoVpKl5Ui/ml/6O8z/o/Gsz9OAiTtjnYphbwqudSPlu/siev5nDHxlBXuPa1tKClE6T1ADZLYev3HSm7BysdZP/BFhqHCH6nez5yUVpkMDaxcg5+r7zySs4//3zOOOMMXnjhBdatWzfgMTU1NYM8UwxnpAT0ibRFNGmyqMbZMwMlB4cYTD6zagNmHMoyM64726K83hJiYY2fmX7X8LPHvYshDLUOt1cxiHzafqArxpNb2/jvf+zJ/WpHLu2xu8BMZDbl0Z0nuNZPc0ccMxkmbtloNTy8qaGCjliKg8EESqkxb14sduCVHUA89dc/cc6Bn+JXYTr1SuzumTSUQ3loW07ZN3rrvRRGAc2dMQxT4XHaegpRZEpygE3XeMZYSHjWeuYYTfisCFHdzw6rnmDY4l05fK6hLv+uWlDFq5vaucKwYWlxYmk3Nl3D47Bht2X+tjykSGEnpnw5fZ7BSNUwMZ5kMDaxcg5+b7nlFs4880y2bt3Khz/8YdasWVPMdk0bw52Qo0mThGGi62D0KzRQiINjMqwjnmiT7TvKZcZ5qBmHWYFMudyth8Ps74iRSJu4RlqTOXeEdbh5zDRm276pqaNPGdy8rnYM1543/ws8/9+ogy8T9blIWwqHTSfgdhCYbSd1pJVw5fFcu+YCFtcG2Ly/s2CbF8cj8FrRUMGbyv5GqixNzLeYKrsNX3YdtarIKftGb9m1xPGUQSxtEoob2LO73DQNU2UyOyjAbbcRTRpEUooD7gU9r+GyFKlobMTPNdTl301NHfxly2HKnFW8lXqO1fayHzeGpYimDHzOTGrBMrODHbYFzK4bfGNl788z3fORi9JQKoOxyfYbVyh5ZXu44IILuOCCC4rVlmlpuBNy2rIwLYVN03DYBv5YjeXgyHWR/XQ9MGDqbkQYbsahwuvkuNnltEVSXH16/5yrQxhuHW6eCnIpcJj2bD0cwbXzDWyd22ingrTuosJh0uAM4ymbgevMa6ieXQEUdvPiuARebVvQ2rfhqpiNy9nvBzXH7Bu9La4po8rnZPP+TixLkUhb6BokdQ23XcdQ4O1O/6aUwlKZc1a+n2uoPvc6bRimIm1aWNh5yHEec4y7mKsd5ohWQUw5IBWlxh6iU3l5afb7Ob02MOznkXzkolSUwmBsqv7G5SKv4FcU3nAnZLuuYVkKn9tW0IMj10X2k/7AsCxo3Zr5/1u3wuzlOQdkU3kjwkgzDh6nHV1LMbfKm/sVhaHW4eapYJcCdR1r5rGZgVs0TUBFCCfSfOsFL3O0K7jM+QgN5n5sVpB40s7zViM1b7mGpf1mqgu1eXFcAq8CZN/obfP+TlrDCQxToTh65cmwFJFUplzyvBk+mrtiBONp7LqGo9fxlevnGqrPIwmDUCKNXdeJJC0OzDieW7qu4DL1CAu1A1RpaZLKwWtqHk8GLuJ97zx/xFy9vddGV/ucmN0lo0NJY9ACIkIUy0QPxqbyb1wuJPidYMPtdj8SSeJz2TMlQbsvNWaN9uDIdWbNUopv/Xnr5D0w9m3MXPpu3wOzPgsPfxZmzB+0xG1/U30jQinMOAylUJcCBxu4BeMplIKKWSu4izdRl96Lz4oQ0fw8E57J8l2V3PpmNaBPC7F5cVxyQBcg+0ZW9hgwTMXyunIOdMZpj6YwLYWmZQYiLrtOwGNH4aGrpz8UZncp5Vw/12B93hVLs/tIhETaQuteaXEolMQKnMR/RJcyO70XvxWh0/JSMecEPnfO0pzOR9nZ/Fsf38ErzV0k0iag4XbozJshxZrE+JnI4lBT/TcuF/lflxQFlz0hL68LEEoYNHfGCCUMjp9TwRfOWUJtuZumjhjRpIFpKaJJg6aO2KgOjlxn1n78xK6eA8PnsmPTNXwuO41VXoLxdCZA7rcOuWTs25jZ3HPwZXB1By2u8qMlbvdtHPbp+cw+TkbZGYe2SBKl+vZhdlC1qMY/IZd/ewfmg8klMM/OaLx2IEi52059pRe7rtEWThFKpAnGDZSmc8C5gO3uE2hxLaC6zFP0Ph3qOD+uLlCYwWQ220W4NRMt9pbNvjFz6YjZN6DvMVDpdbJ8ToDFtX68ThtOu47XYSNlWpmBSDxN4wwvJzVUEk6aeX+u/n3eFUuzozVMPGX2jPc1LZOG72AwzpwqH87Zx9M+483EKpfy1QuW5/3dRZMG5R4HC2v8nFgfYNnscg4GE9z0py1saurI67WEGK2inxOGMNV/43IhM78lYrjLq0tnlRWsaEIuM2sHuuJEkwazA+7JtwvVsjIzvj0lbruDJKcPquYXtOTuZN0VXsrlqMd6KXCoGQ27TcOmg2lBc1eMgKe8z2uPV5/2Oc6jSWoSu2n0RtHdB8GqGNU66R4FzL7R/xjQgNkBDx6nnebOGJGEQcq0CMYNTmqo4IrTGke9PKR3n3sceiarhKXwOm1YSUibFg6bhtdhI2FYNHfFOXZWGUeiFsfPCbC0NvdzUPbvIxhPs7jG3+dvwDdNZrxEaZmI4lBT/TcuFxL8lpChLq8W8uDI5ZK3TdcwLZVZbjGIkj4wxrPk7iTeFV6q5ajHGpgPNaPhsOnYdB2NzKxfNGnidx/t2/HsU13XWJraApuzGSmSmeUI1UtyWpYzrAJl3xjqGKjwOAh4AhwJJwkl0nz5XUs559hZPf0xmsFw7z7f0RYlnDBw2nUslSmhrGmgaxqWAqdNJxw32NEWpabMVbQrXyU5sBdT1njnhZ8Ov3EjySv4vf3223nwwQepqqri6quv5h3veEfPfUeOHGHlypVS4a1ICnVw5DKzNr/ax6FgYnIeGONdcncSK9Vy1GMJzIea0fC57PhcNkLxNJqm9clKMO59ml2WE+/KDNKys7PZZTl55OIdVAGybwx3DKAyacZOrK/oE/jmxLIGbVe2z295bDutoSTKMLHpOgGvgwqvk65YimjSxLQsTAsaq7xcv2ZxUa58lezAXogCmS6/ccPJOfj94Q9/yPr167nqqqsIBoOcd9553HDDDaxfvx4A0zRpamoqWkNFYeQys/apMxZyz7NNk/PAmIiSuyMo5XRxE1WOeqTvZLSB+VAzGhpQX+llayJE2rQwTCvvjVkFMWBZTvf7Of2ZqnR55uId0hizbxRlaUx2E+oQs93ZAPiaX2/Gbdcpc2dKS2vAnAoP0aRBOJEmYVhsOH8Zx9YNndZsKDLjJURpL30bLzkHv3fccQd33nkna9euBeBTn/oUF198MfF4nK9//etFa6AovFxm1nSdyXlgDChx2+u+ApTczXdZwKRPF1cEL+3v5J6NB0b8TkYTmA83oxFw26noDmrSpqK5Mzb+Sz0KsCynv2IMrixL4XPZufjkOTyxpZXDocSYlsZYTc+S+PN6tHgXlr8Wb6AWzUwMmO1eOquc4+oCvN4SZFZ3JTnIHMY+Z2ZW9vi6wKgHbDLjJURGqS59Gy85B7979uzhtNNO6/n36tWreeKJJ3jnO99JOp3muuuuK0b7RJGMNLM2aQ+MAZt+5oAPSEUhfGBMJXfzDSymWx7FXIOwmx/dRlvULMp3MtKMRm25m/XvWkaZxz4xM/EFzsVbjMHVYK9ZU+7i2LpyPA4bteVuPA4bljUwLdygr7f3COqB71ITbeUAs9DjBj5nlPoqDxX9NqHqul7UGSmZ8RLiqFJd+jYecg5+q6ur2b9/P/Pmzeu5bfny5TzxxBO84x3v4MCBA8VonyiikWbWJu2B0XvTT/uezG3J0JhK7uZrtHkUS3mJxHByCcKyqfGCcYN5M3xFyy1Z0gO3AubiLcbgarDXbIskeW5PJ//ccaR785mO26FzQn2Az509/LrbTU0d3POHR/h0dDchWxUemx1TKcIJgx2HIyyq9VPRb7a72P1X0n8fQoyziVr6NtFyDn7f+ta38sADD/C2t72tz+3HHnssf/3rXznzzDML3jgx8SbtgZHd9HPwdXhhN7z7B3lVeBur0ewqn6xLJHINwna2RQCo9jv7Xm4GoikTl13n1ZYgWw+FRrWes7eRBm4TNsgYsCyn70ayXJflFCNJ/WCv2RVPs/dItCcHr13XcNs1UqbF83s7Wf/gq3zrPccP+veZfT09HsSnm8RsbtDApml4nDbiKZPmjjiBWT60frPd+Qy8R9OXk3ZgL4QoiJyD36985Sts2rRp0PuWL1/Ok08+yf/8z/8UrGFCjJmuQ81SYHfmfwsQ+Ob6Q5vvrvJSXiIx3GfOJwgLxdM9nz1bgqErnqa5M9ZnJ/9Nf9oyqp38ubZ5QgcZBcrFW4yUXf1fUwHNHTES6UyxCR16ljr47DZiKYOWrgR3DxFkZ19vua8SI+jAqZIktaPLPZx2nWjKIBaP4htktjuXgfdY+nLSDuyFEGOWc/B7wgkncMIJJwx5//Lly1m+fPS7i4Uodfn80Oazq7yUS02O9JnzCcLKPQ5auz+7y2mjK55mx+Ewhqlw2nXsuo2UYdHUERtTwD9cm4GJH2QUIBdvMVJ29X/NTHYFA0Umzy4olOqutA647Jn+eq0lyPbWMItryvoMODqjKVKGyRH/Alric5mb3EmrVtcz223TNFKmQou0QuObema7swOXrmiazniKCo+DSp9zwECzlAeMYnqZrMvVprMxFbno7Oxk586dzJ49m/r6+kK1SYiSk+8PbT67yks18X4un9kwVc5B2ElzytgJtEdSzKp0ZCp5mQqP0wZKETcsyjx2Fs30sa8zPqqAf7g2/8fDW/C57KUxyBhjLt5ipOzq/5pp08LqLpOcCX0z/5v9E7XpGgpFMm3y3O4Obn9yV99NcmUuDEsRNxRPlF3MpemfUGO0ELRVkdJc2MwEc+gAT23PbHd24PJKcxdHIqme6m7Vfhcn1Ff0DLpKecAoppfJulyt2Ep9QJDzdeCvfvWrxGIxANLpNB//+Meprq5m1apVNDY28p73vIdEIlG0hgoxUfr/0Ppcdmy6hs9lp7HKSzCe5pdPN/Vs6IKju8oDHgdNHTGiSQPTUkSTBk0dsT67yo/OuA1dUS9lmOOaeD/Xz1zmtvcETIPpHYRlT3zlHjs7WyOE4wYOW6aaYNywsOsa9RVedF0fVW35kdp8JJLkleYuZvZbcwwTVM8+m4t33lsy/zuKIhRtkSRKqT73ZQdXi2r8eaXs6v+aDpvePeMLlsrM+tp1DVv3baal0Mgsj/j1c/t47UCQcred+kov5W47+ztiBONp9nfG2Ok6lt9WXc0+10J8VoSZxiFcZphW3xLc530T5q7qGbhsauqgLZzENC2cNh3TgiORZJ/78xkwlirLUmw9FGLj7na2Hy7ddoqhZf8m+//tZycINjV1THQTJ8Smpg6uu/8lrr//ZTb8/lWuv/9lrrv/pZL6PnI+237nO98hEslsWPnP//xPHnroIX73u9/R3NzM//7v//Lcc8/xn//5n0VrqBATZbQ/tNld5cvrAoQSBs2dMUIJg+PqAn1minvPuA1mIhLv5/qZ0cg7CPvCOUuYW+XFsCzSpsKwLMrcdhbVlPXk4R1NwD9Sm8vcdhJpE1MN/vyJGGSMVj6Dq3ycsWQmuqaxozWCUgq/KzMgs1RmxtftsPWsB04ambXAGpA0rIEDjhlevE4bsZTJ3vYor2hLuKPqK9wW+ALfdVzNjyu+gPben6I3ntpn4JI2LZQCj9OGTQeHDoapSBsWXbEUv3y6qWdJRSkNGAfTO8DdeijUM0DuHxx89cHXgEwObDE5jGZSZDqYLAOCnJc99P5h+93vfse3v/1t3vOe9wBQV1fHLbfcwo033si//du/Fb6VQkygsayvzGVXeSkm3s/1M4fjRs55U83u2P6khko2vHsZ19zbu5JX3889moB/pDb7nHZAI5Y0CHgGvu5kq+5VyJRdvS/dxlKZtb7BeBqXXcdh00mbFrqmZUpDmxbJ7gC1piwziz7UgKOh0suhUIK5VT5aw0mOGCaH7Q0smrusTxuzAxe/y05rOImuQaQ7oM/+8rTHUpS57exojdAVT5d8pbbBLocfM9PHvGovj7x2mHjaZE6FB4/DhWFkzh03P7qNL51nn9aXyyeLUl2uNpEm03KkvNb8Zj/I/v37WblyZZ/7Vq5cWdTyxp2dnVx77bX84Q9/AODCCy/ktttuo6KiYsjnPPjgg9xxxx1s2rSJ9vZ2Nm/ezEknnVS0NoqpaazrK0faVV6Kiffz+cxLZ5XnHYQtrS3nuDndlbxchQn4R2qzrmu4HTqhpMEspUpikDFWhUjZ9dL+Tr71yI6eddI1ZS7iKYMDwQQeh43LV87lxaZOXj0QJJYygMz3eGJDgLOPncUvn9477AysXde4+vRjqPA5hmxjduDidGfWGpuWQinVM7OMAtOCg6EklV6LSo+z5AaMvQ2aLzmc4K9bD5NMW2iahsueGVTUV3qp9mT+XkNxo2SCAzG8Ymw6newm04Agr+D3zjvvxO/343K56Ozse3kmGAzicg3+R1AIa9eupbm5mUceeQSAj3/846xbt44//vGPQz4nGo3ylre8hfe///187GMfK1rbxNQ2HjOzpZZ4P9/PnG8QVoyAf6Q2H4kkObEhQCRhlMwgoxDGmrLrvo37B8zU+N0OFrvsNHXE2Nce4+6rVrK9LczrB0IALK8rZ+mscra3hvnNc/vpiKaw2zQcNh2fy95Tljg7SKrwOYZtY3bgYpoKozvw1bWjEy6ZzXYK08oUyCj32ktmwNh/Y8/Cav/AfMmxNPs741hWZgmJXcusqc4U+wjjmOUDYIbfWTLBgRheMTadTnaTaUCQc/A7d+5c7rzzTgCcTicvvvhin4IXTz75JEuWLCl8C4EtW7bwyCOP8Oyzz7JqVSYN0J133snq1avZtm3bkO+7bt06APbu3VuUdonpYbxmZksp8f5oPnO+QVihA/5c2nzdWYsBSmaQUQq2HAzhttuIJs0+y096z9TsPBLh2NkBjp3dt/hIOJEmGE/RFk5h08Gm6/hcNuorvQTc9pwHhtmBy4tNnWRTqmnZvy2V2XBn1/Xu7XWZ20phwDhoKegyF3vbo8wqd2fWRyuVyWxiKZw2jZRJz7pzj8NGPG1yoCsOs7vXKofTJREciOGV4nK1iTaZBgQ5B78jBZCnnnoqp59++ljbM6hnnnmGQCDQE/hm3y8QCPD0008XNOhOJpMkk8mef4dCmZmOdDpNOp3bCSn7uFwfL4qnUH1xQl0Z689dxH0b97O7LUowmsBpt3FiXRkfWNXACXVlo34Py1LsbIsQiqcp9zhYONOPPiNTDMA0jZ61suOt0J95sL44oa6M/3zP8oGfX9dG9X3m0magoO85Wb24tw2AI8EoJjYO6+B12plT4elZE+13agSjBu2hGK8bRp/v65UDXdz86DYcmqLMmVmWYNcVyWSKPYczg7eaMhcfWjUnp7/jdavmsPNQkE4bWJoCTfUEjw4NHJrCYdMo89gIRhOk094Bfz9+jx0URBJpXm8+wkJa0JNBcFdA9eKCVnh8aX8nNz+6jWDcoNrvxO1wkEib7G0L0RFNUeOzY0cnkjIwjDRlDh1QGKbCUuDQLBy6jt2hYaQNAAwjjc+h43dOr7/FUpLPb8a6VXO4+dEIBzujzPA7ewbb7ZEU1V57zn/7U8X8SjdLarxsPRii3OkZMCAIRhMsm13O/Ep3Tt9vvr/f+Rwzmuq/RbsEffOb3+Suu+5i+/btfW5fvHgxV111FevXrx/2+Xv37mX+/Pk5rfm98cYb+drXvjbg9vvuuw+v15t324UQQgghRHHFYjHWrl1LMBikvHz4q5B5rfl9+eWXefHFFznjjDOYP38+r7/+Oj/+8Y+xLItLLrmEc845J6+GDhVo9vb8888DDFg8DXRviCjsJeH169dz/fXX9/w7FArR0NDAmjVrRvwys9LpNI8//jhnn302DsfET+9PZ7n2xUv7O3tmC7OXLxfM9LF2VQMnNVQWpW0DZ46OzhqUe+x84ZwlRXnvifisIMfFuLMsOLIdEl19Zj4tS/GVB19l56EgH10Q5ofbPHTEutOGKUXCsPC77Syt9bOzLUo8ZVLhdfb5G20JJuiIJJlX7ae2LLO+TylFNGViWFYmNZmp+NZ7j2dxbe6XfS1L8eUHXuHVA0Fm+BwYFjhsGnabjtdho7kzzrLZ5XzrPcf3WXLT+1g61bmHyyN34TUjtKkAps3NwiqdsnQXeMrhHf8O9W8e01e7/XCYrz74GmVuW3cWkaMU8OqBLiIJg+PrA2hobD0Uwq7r6LqWSUunFE6bjtOmZ9Y3K4v1J6X57cFKrluztKjHoRjeaM5Tg169m2R7BwppsN+YY2b6+ECevzH59kX2Sn0ucg5+H3jgAS677DIqKipIpVL8/ve/533vex9vfvObsdlsnH/++fzyl79k7dq1Ob/5Nddcw+WXXz7sY+bNm8crr7zC4cOHB9zX1tZGbW1tzu+XC5fLNejGPYfDkfcP9mieI44qZIWY4fpiU1NHn93ulX43ibTJKy1hmh7ZUZQyqZaluGfjAdqiJvNm+Hpyp7qcNmZXZnK3/mrjAVbMm1nQk+hEfNb+5LgonCGPkX0be5VPTmbKJ1cvgZUfZ6tzGdtaY1T5XECYmeVe2mJRgslMUQk0G+1Rky2HY0RTFl6nnbrKvn+jAa9if1eSllCSqjJPZoObBu7uvMCmlVnnGkmpvPt63VsWcNOfttAeT/dZt727I0HA4+SDp83H5XL2+Q6yx9L8Kg/ntv+BcqODVntdpoRyKk1LyM7y2XVonXvhxZ9B46oxLYGIpBTRtEWl343BwONzVoWfLQdD7O1I0lDpwWZ3EEyk0QCHzUZ9wENXLEU0ZZA0LCpcmbZct2YppyyoGXW7RG5y+W3J9zy1vH767RcYyikLalgxb+a4/H73f1yucg5+v/nNb/K1r32NDRs28Jvf/Ib3ve99XH/99T15fb/3ve/xn//5n3kFv9XV1VRXV4/4uNWrVxMMBnnuued6Uqxt3LiRYDDIaaedlvP7idIz1ElovEpGTlRewolICTOZcjCKkQ11jHzqmCMsfeU7mbLJZbVg94ARh4OvwGMbMI/7Eikjs0YVIOB2sKi2jObOGNGkiWlZmBbM9Luwx9M9G7d6c9psOHSdSMIkmjTw99rcooCOaArDUnTEUliWyuvvKd+NbL2PpTlGE3WpfQRtVT11mJ32TFaFg6EkAdcMvK1b0dq2ZKrqjdJIG3tcdp1ZATfzZmTyGztsGhoaNl2jocrLTL+LCo+9J53cJ9/eCAdelhnfcSDliMfHWLPQFFvOwe+2bdv44Ac/CMBll13GFVdcwcUXX9xz/yWXXMKNN95Y6PYBsGzZMs4991w+9rGPcccddwCZVGfvfve7+2x2W7p0Kd/61re45JJLAOjo6GDfvn20tLT0fAaAWbNmMWvWrKK0VeRuqJPQqgVVPLCpuU+OzETa7KkQU8jZyYnKSzgRKWEmUw5GMbzB8sgm0iZvHOikde9tNLra8dQu6gkAcfqhygcde6jfeS8u20f6VBSs8DgIeAJEkwbhRJqEYfGBVY389Kldg+bw9bls+N12OmOZSmt0B4Bd8TT7O6J0xQycdo0f/mUH//fqobwDi+Eyn/QfMHdFjx5LvlQEO2lSWua4MkyLeNokbSp2H4ni1BVz9RDBvftYMobgN5ed/ifWV/C995/IziMRgrE0B7riPLm1lV1tUZo7YzjtNlbMreSK0xo5oa6MPx94edTtEbkZ6rjp/duS3RQrpracg9+ysjLa29uZN28eXV1dGIZBe3t7z/3t7e34/f6iNBLg3nvv5dprr2XNmjVApsjFj370oz6P2bZtG8FgsOfff/jDH7jqqqt6/p1dYnHDDTcULVAXuRnqJPTagS7+saMNr9PGktqyos9OTlRewolICTOZcjCKoQ03g7+INmYf3sd+PcAi6HtBXtOgrIby8C7eWnGEpzqqoNeqMQ3wOTN/A8fXBTiuvnzIv9HMYMlJOGFwJJLCZbeRNCy2Hw6TMi1cdp1FNWW47PqoB62DzRwNlVrMsBSJtElU92PgwKmSRC0X0ZSBZXWXZrbruFWCsKHzXxvbWTerY9SD6FxTAdrtep/PcPFJcwYN6CWzQ/HleuXru+8Z/aBITB45B79nnXUWn/70p/nMZz7D/fffzznnnMP69ev5xS9+gaZpfPGLX+Stb31r0RpaVVXFr371q2Ef0z9xxYc//GE+/OEPF61NYnSGOwlVKxfNnXF0jaOzVt2KMTs5UXkJJyJH5GTKwSiGNtwMvl9F8GgGLWkb0ZTZZzkCAHYPmtnKe5Z5eenFzH3RlIHd7hgQuC2tLR/2bzRhWLy5sZIKr4NdbVH2dcRImxZVXif1lV4quv+OCjVoHWrAvK8jSjCeJm1a+GoaaXHOZW5yJ0eMmVgWoIFd17DrGlVGJ03uRbyWqhtze0aTZ7jULwVPZble+drZFpmgFo5dIffJTHU5B78333wzH/rQh7j66qt529vexv3338+GDRs49thj0TSNY445hp/97GfFbKuYIoY7CRnd6wMTaWvAWkIo/OzkRCUqn4iSxpKUfWoYbgY/qvsxdScOM0natAY+2YiD3cWSeXP5wsyZtLz6DOGESTSdHjRwG7FoyNmLOHFOBXc9s5c7n9rN7ICL+goPeq/NZIUYtA43YJ7n9JE0wsRSJns7EvzZfQEfTP6UOnWII1oFKc1Jpd2kymglppfxZPlFVGueggyiS6kwjRherle+QvHJOQsva5nzk3PwW1tby+OPP97ntttuu43Pfe5zxGIxli5dit2eV+Y0MU0NdxJy6Do2XcO01KA/3oWenRzvILT/yHz9u5Zxz7PjU6FqIgJuUXjDzeC3OOax39bAXHMnDr1fJhylINwKdSfCzGWcVGXS8ip88z3HEUmpQQO3kWY3Aa7/3cu80txFRyxFJGUQiht9Zn5h7IPWkWbtGiq9HAolaKjy8kJ4MYf1K3i3epjFegteWxiFk32uRTxRdhG73MtxW6pgg2iZzZ0ccr3yVe5x0DoB7RuLXNYySwDc15ij1QULFhSiHWIaGe4k5HPZcNtthBMG9n5BWLFmJ8erTOpQI/N1q+dS5naMy8xRKZSEnWiT/dLgcDP4Fhr36+dyvfOX+KL7QO+V7SHcCp4KOOVjmTRf3WWnFteWDZsiaKjZzc37O3t+cMvdDtpsSXQ0wkmDHa1hFtWU9QTAuQxah+uXXGbt7LrGJ05fQKXPyavN8/j+k8s42X2QmY4EUd1Pi2MeSsvk1e2IJkmbo8tGISanXK98LZzpZ+cEtjNfksVndAo2VfvCCy8Qi8V4+9vfXqiXFFPUcCchALdDx1I22iMpdE0bl9nJYl++HG5k/q0/b2XD+ctYtWBGQd5rJNP5Uu1UuDQ44gy+/wSSb/462r7fdOf5bc3k+a07MRP4zl018psM8p69Zzf7/+CiaRwOJwgnDNx2nYRh0dwVI+DJPGekQetI/ZLrrF2lz8nSWeUsrinjHzuOsLlFp9F/NCDoiqVp7ozRGUvhtNu47a87B81GMdkHSGKgqXrlS7L4jE7Bgt9169axfft2zOlSxFqM2kgnodpyN+9dUc/G3R3jOjtZrMuXpTgyn2qXanMJVibrpcHBPttIM/hLG6vgze+Eti2ZfL+eCpi5bEyFHXob7Ae3vtLLjsNhEoaFTdOIJA2ORJJEU+bRwAIFh9/o06ZN+7tG7JeTGyrzWq8+2DkmaVjsaA2TNDLFPBbV+nHZBmajmAoDJDG4XK58TbbMG5LFZ3QKFvz+9a9/nXR/NGLi5HIS+sApc6fE7MtUG5mX2qxYLsFKKQ5AcjHSZxt2Bl/Xewo5DNZnYzHYD26F52ixjEjCIGVaBOMGJzVUZI5pbQc82LfqnJqxhKfCZ9AVaxi+Xy6rzHvWrvc5ZsfhMPs7Y6QMRaXXQUOVjwrPwGwUllJ8689bJ90ASeRuql35kiw+o1Ow4Leurq5QLyWmiZFOQlNldnIqjcxLbVYs19nc8RiAFHpQkOtnG6m9Q641XzVn1G0b6gc3WyzjSDhJKJHmy+9ayjnHzkJvfg4e2wDxLpS/lqjTgZmMYdv3IufEXqOz4uMc0E4AQFMWdem9+KwIM1we3jissb01PKr16tlzzKNvHOI7/7eVcreD6jJXn/zHvfv/x0/smnQDJJG/qfLbApLFZ7QkPYOYUFPpJDSUqTIyL7VlA/nM5hZ7AFLoQUGhZqqH67ObH42wdpRzFsOu21eKaMrgxPqKTOCLgud+CvEuujz1NB9JEE0lsSxQViW11kHeGfkD9/iPY0FyC+8IP0Rdah920qRxsFPNwdz7GZi1JudZu/4DkUqPM5Pn1+dksG/L7bBxoCtONGkwOzCwnPNkvEJTLKV25We6m6prmYstr+D39ttv58EHH6Sqqoqrr76ad7zjHT33HTlyhJUrV7J79+6CN1KIyWwqjMxLcdlAPrO5xRyAFGNQUIiZ6pH67GBntOdxwxkq2Mn5B/fwG3BkGyFHFTtaoximwmnXsdk0Uia0JSuoSezl+I5HOT/5Z7xWhKCtipTmwmYmWGTtpnrzt6AuAHNXjThgHqkK3FD9n02xOFg5Z5hcV2iKpdSu/IgMyeKTv5yD3x/+8IesX7+eq666imAwyHnnnccNN9zA+vXrATBNk6ampqI1VIixsCzF1kOhCZmtmAoj81Jct5zPbO4p86qKMgAp1qCgEDPVI/XZDL8TgJ1tEZbXD/7jOFKwk8sPrhXrJJ2IsyvuJmUofE5bT/VGp91GNO3CoTo5NfwYXnuEVntdz/1hywXuehqMdnj+Tqg/ZdhNe7lUgetdNh2O9v/8ah+HgolJf4WmWErtyo/oa6qtZS62nIPfO+64gzvvvJO1a9cC8KlPfYqLL76YeDzO17/+9aI1UIhC+MqDr7KtNTZhsxWTfWReiuuW85nNLdYApFiDgkLMVOfSZ8CQFa1yDXaG+8Hd1NTBY38/zPtCJkkjSkpzYyUVHocNuy0TxAYcBnpKo9pq5wgzgMwMbMqwsNs06md40Wx2aNuayV7RvYmvv1yrwDW1x5hZNrD/P3XGQu55tmlSX6EpllK88iMGmg7LCAsl5+B3z549nHbaaT3/Xr16NU888QTvfOc7SafTXHfddcVonxBj8tL+TgC2HAxR4XNP6GzFZB6Zl+K65XyXkxRjAFKsQUEhlsrk0mcA5Z6BfZZvsDPYD242eA5GKzm1u+pcszYLw8qsCfY57Zl1uKqLVmcNZalWopYD0ia6DmVuO/VVHio8TrBsmXzF8a4hP28+VeBaw8lB+1/XmdRXaIqlFK/8CDEWOQe/1dXV7N+/n3nz5vXctnz5cp544gne8Y53cODAgWK0T4hRsyzFfRv3c4YX5lZ6MLXMTNdUza9bzI0opbhueTSzuYUegBRrUFCImeqR+qw9koJaWDjTP+C5Yw12+gTP1X6eiFzMe4/8Fw0cpl2rIKYckIpSYw8R08v4p+cszjUfoLFcx7B7cDt0qv0u9Ox7G/FMoQ5PxZCfN98qcIP1/2S/QlMspXjlR4ixyDn4fetb38oDDzzA2972tj63H3vssfz1r3/lzDPPLHjjhBiL7a1hdrdFOaORKT9bUeyNKKW6bnk0wUohByDFHBSMNRAbqc+qvfaex/U31mCnf/B8oOwEfhT8MBen/8xC7QAztDRJ5WCXfSFPBS7i/7rqWcyzLA3t5QCz0G0araFkZubX7ciUZq47MVOoYwj5VoEbymADpIXVfnYeibBxd/ukumJTKKV45UeIscg5+P3KV77Cpk2bBr1v+fLlPPnkk/zP//xPwRomxFhlf8CHMlVmK8ZrI0qpzopN5HKSYg8KxvrZhuuzD62aQ8urzwz6vLEGO/2DZw3onPEmNhw+hnnWfqr0KB2WD8O1mK6gSWc8zQPu8/i8uoe56jDtKkAo5qQpEcbli+Mpn5EpzTzMZrdCDkR6D5A2NXVw/e9entYZDkrxyo8QY5Fz8HvCCSdwwgknDHn/8uXLWb588I0IQkyE7A/4UKbCbMV4b0Qp1XXLE7nRo9iDgrF+tqH6zDQNWl4d/DljDXYGC54rPA4W1gZo7nSwI25gWBZzjEyatUqvg3TtKdwVcnF61++ZazVTS5qkaeepyFzmvuWzLJu7atjPWYyBiGQ4yCjVKz9CjJYUuRBT1uKaMhbM9AGdKKXond1+qsxWTMRGFNlRPFCpDgqyBuszc+iLImMOdoYKnis8Dsrd5exsjTC3ysvaU+fy4yd2Ue62E4wbvNDZwP9an2aZfoAKLTM7/HqyjgXPuPiPWR0jBpqFHIhIhoO+SvXKjxiZFCYZSIJfMWXpusbaVQ20vNrM/s44AZ97ys1WyEaU0jHVBgVjCXZGCp5nlrm4fs1iDFORMkxcdid7joQxLIXHbmevNg8ApYNuGQTj6ZwDzUINRMZzYJktNPLC3g4qyzwlG5yU+iBPDCSFSQYnwa8YlckykjypoZKWV2Hp7HK2tcam3GyFbEQRxTSWYCeX4HnroRBOu42OaJJQIo1N0zCVwkYmwDQthU3PZH7IJ9AsxEBkvAaWm5o6+NXTezjDC1//4xtoNntJBydTbZA3lcmynaFJ8CvyNhlHkt9+z/Hs6UyUfLCeL9mIIoptLMHOSMHz4poyqnxOXmjqIJG20MisTtJ18DhsmCqT77fS5+RAZ6xki6iMVjY4iSVSnHEMzKn0EEkpCU7EmMmyneENvXVWiEFkT9avHQhS7rZTX+ml3G3vOVlvauqY6CYOKvsDvmrBDJbOKp8yB3v28nLA46CpI0Y0aWBaimjSoKkjNiWWdojJbbhjb/P+TlrDCQwzc9lfARZgWBBOmpiWor7SS3KIQDNbtnzj7na2Hgr1LB/I9zGDyQ4s2yLJzJ6BXrIDy0U1/lEPLHsHJ3MrPQDYNA2fy05jlbdnqUeu7RWit3yW7UxHec38vvzyy/zxj3+kqqqKSy+9lOrq6p77QqEQ1113HT//+c8L3khRGmQkWZpkI4qYjLLnk0jCwGnXMVMm/cM8w7JQlkVbzBhwBSOXK1BjuUpV7AwHUjVNFJPsBxlezsHvY489xgUXXMCiRYsIh8PccMMN/Pa3v+0pbhGPx7n77rsl+J3C5GRdumQjytQ0Hmvrtx8OE0mpcf+b2d4aZsfhMEnDAqDMZSeaNlCquyiNUlgWbDkUYcksP6cvmcnzezsIeB2EE2m+9eetw65lBMa83rGYA8u+wcnA2d3pHpyIsZH9IMPLOfi98cYb+cIXvsBNN92EUoqbb76ZCy+8kN/97nece+65xWyjKBEykixtshFlain22vqX9ncC8NUHXyOatnJ6/UIG48FYmkjSIGGYOG06dl1D0x3E05nlDopMSGhaFomUxZ1P7SZtZtoZjKdQCpbOKhv0CtTd/28vCgpylapYA8vewYnLNXAF4nQPTsTYyH6Q4eUc/L7++uvcc889QGZU/sUvfpH6+nre97738etf/5qVK1cWrZGiNMhIUojxUexd2puaOrj50W2srYMyt41Kv3vE1x9rMN4/cC5z29G7Mzq4u2vROHQNu8tO0jBJpC0spUiZip1tYQIeJ3OrvJiWoi2cwmnXCMYNKnqdb7JXoF5rCYFGwa5SFWNg2Ts4KXe6+9wnwYkYKylMMrycg1+Xy0VXV1ef2z7wgQ+g6zqXX3453/ve9wrdNlFiZCQpRPEVe2199vWDcSPzuk47Btqwrz/WYLx34JxMGyg0ZpW78Dh1LEthKrB3fxTDUsTTJlZmNQQa4HHYiadNdrVFmBVwY9PBtKC5K0bAU97nXOR22EimTdAy//9gSuEqVe/gZH9nHKrAVIpoypDgRBSE7AcZWs7B70knncSTTz7JihUr+tx+2WWXYVkWV155ZcEbJ0qLjCSFKL5ir63Pvn613zngvsFef6zBeO/A2ePQCSdNIgmD/Z0xUAqFRiRp4HPasNl0YikDyzpakNFu03DaMknQ4oZFeySFrmnomkY0aRBNmvjdR3/KEmkTl8MGGiV/lSobnPzq6T1AiAOdcTSbXYITUTCyH2RwOQe/n/zkJ3nqqacGve8DH/gAAD/96U8L0ypRsmQkKURxFXtt/dHXHzzw6//6YwnGewfOlV4HO1ojGJbCaddxaxqRlImyFJaCaMpEwyRtKez60SIXHsfRq0xOm07SMHE5dOIpE03TSGeniOl9BaocBbxxMDTsVaqF1X62HgoVLSjIZY30isYqjpvl55FHmvn3C44t6QpvYnKS/SAD5Rz8XnLJJVxyySVD3v+BD3ygJwgWU5uMJIUonmKvre/9+oPp//pjCcazgfNMv5O97bHu8sU6aUsR7c7jmw1dLaXInkIU4HXYSJsKvVfgatMgpaDa7+JAZ5y0aWGYFqal+lyBuvIt8wCGvUq1ckEV1//u5aJtKMxnjXT23PnmeVU4hhiUCCEKJ+ciF52dndx2222EQqEB9wWDwSHvE1PTVC0aIcREK3Zxhezrt0dSA+4b7PXzDZZ7F5V4tTlIMm1gKoimDJw2nYRhEU4YpHsFvlkOPbPEwaZrKKVwO3RSptWTCMxUoGtQ4XFQ4XUws8xF2lQ0d8YIJTK5gLPrj7NXqZbXBQgljD6Pee+Keh7Y1Fy0Yj2TtRiQENNFzjO/P/rRj3jllVf4zGc+M+C+QCDAP/7xD0KhEBs2bChoA4UQYjop9tr67Ot/988RIBOU2u2OIV8/n42u/Wc7LeBIJJWZ4VVgWRaxQYpZZJlKYdN1bJqGYSkcNrDrGvG0iUPXSJkKrzMz01xb7mb9u5ZR5rEPeQVqsKtUC6v9XP+7l4u+oVCKAQlRunKe+X3ggQe4+uqrh7z/E5/4BP/zP/9TkEYJIcR0Ntys5VjTnGVf/wvnLAEgnDCHff1cS2hv3t85YLZzpt+FpeBAMIFSilh66MA3SyOz/EEBibRFXYUHj0Mn3p36rMxt5/g5FWw4fxmnzK8a8QpU/6tUO49Eilr2VcrKClH6cp753bVrF4sWLRry/kWLFrFr166CNEoIIaa7Yq+tP6mhkpZX4ZvvOW7ECm8jbXQ9uaGS6+5/acBsp99lZ3Gtn9cOBEkZFuYIka9pZWZ66yo9dMXSdMVShBNpass9nFDv4swlNaxcUDXm4hrjs6FQigEJUapyDn5tNhstLS3MnTt30PtbWlrQ9ZwnkoUQQoxgPHZpL64ty2mT1XDB+NZDoSFnOyu9ThbVlrHzcBhzhOhXdf/fSo+TSo+DNpedT55xDMfXBwoW+I/nhsJSTrMmxHSWc7R68skn89BDDw15/+9//3tOPvnkQrRJCCFECRpqo+vR2c5MUQnLsmgNJdjXEaM1lGCG10GFz4kth9jV6bDhdeociaY4fk6A976pvqCbasdrQ2GxXl8IMXY5z/xec801XH755dTX1/PJT34Smy1zkjNNk9tvv51bb72V++67r2gNFUIIUZp6z3Z2xtLsbY+SNi2UAk3LLGXwu+y47DppM7P8IXuf1W8yuNLjYF9nvGhFc8ZrQ6EUAxKidOUc/L73ve/lS1/6Etdeey0bNmxgwYIFaJrGrl27iEQifPGLX+R973tfMdsqhBCiBGVnO5/edYTOaAqrOyVZduNaylR0xtI4bBpGd34zRXcADD2b4Gw62HS96EVzil2sR4oBCVHacg5+AW666SYuuugi7r33Xnbu3IlSire//e2sXbuWlStXFquNQgghSpiua3zw1Ab+77WDmCpTjELXNZTKXOrPBrgpU+G0ZW43lSK7KqDMZcPttLO4xs+Gdy9jaW3xc4cXe0OhFAMSonTlFfwCrFy5UgJdIYQQPSxL8WpzCNUd+NJdmljTNOw2HWUpjO71DXZdBw3cWiYkTnYXsaiv9HD9msUsrS0ft4Cx2BsKpaysEKUp5+A3FovxxS9+kYceeoh0Os1ZZ53FD3/4Q6qrq4vZPiGEECUsW9hi4+52DEuhk1m+4LTbcNgye6rDSQO9e31vld9J2rCIpgwsBXZNR9c01p3aCMB1979UtJLDQggBeWR7uOGGG7jrrrs4//zzufzyy3n88cf55Cc/Wcy2CSGEKGF9yvh67GgaoIFpKZJGZkbXUqon64GmZTa0La8rZ/nsAEtnlXFsXTkz/U4iCUNKAgshxkXOM78PPvggP/vZz7j88ssB+NCHPsRb3vIWTNPsyfwghBBieuhfxlcpxb6OOCnDwqZlgt542sTrsIECC3Dadar9TjRNw+/O/PxEkwZOu40ntrZKSWAhxLjIeeZ3//79vO1tb+v598qVK7Hb7bS0tBSlYUIIIUpX/zK+uq4zb4YPXaOnkpthWKRMC9Udr86b4e1TDCmb93ZWuZvWcFJKAgshxkXOM7+maeJ0Ovs+2W7HMIyCN0oIIaYry1KTIkPAYGV86ys9AOxtj2aCXiBtWlT7nLgdNgxLEU0aPXlvW8MJXHYb82f62NkWYWaZlAQWQhRfzsGvUooPf/jDuFxHT06JRIKrr74an8/Xc9uDDz5Y2BYKIUSBlHpgmd08Vmobvgb73oYq41tf6aEu4KK5K04obvCxty/gw6vn8fKBrj55bw1LkTYtLAWPv3GY1nCSWMpgXrWfCk/f0r9SElgIUUg5B79XXnnlgNs+9KEPFbQxQghRLKUaWPZu301/2kJXLE1NmQu3w0UibfZs+Npw/rIJaedQ39u6UxtZWOPn9ZYgXqetz3IFTdOwFJy6YAYfect8dF3rk/f2ud0d/Pq5feiaRk2ZC5ddJ5YyCSXSbD8UYvGs8p4AOLs04ri6gJQEFkIURM7B7y9+8YtitkMIIYqmVAPLrP6bx0plw9dw39u3/m8L711RT3NnLOcyvrqusbimjNuf3EXSsPp81nkzfOxoDRNPm+w9EuG4ORUkx1ASuNRn+YUQEyfvIhdCCDGZlGpg2Vv/zWO99d/wNV5FE3L53p7b3cH685ZyzzP7ci7jO9RnrfA6WFRTxt72KJGkwe62CGVux6hKApf6LL8QYmJJ8CuEmNJKMbDsb7DNY72N54av7Izpq81BXjsQZGZ3arLeen9vZW4H37/spJxnWXt/VqUU0aRJ2rJw6DoBj53j6srZfSTKR946n9XHzMh7xrbUZ/mFEBNPgl8hxJRWSoHlUIbaPJY1Xhu+es+YBuMp2sJJIkmDhkovFf3eu/f3lk8Z3+xnbQsnOBJJ9VR60zXwOe1U+52UuR2sPmZG3oOR8Zjll+UUQkx+EvwKIaa0Ugksh7O4pmzIzWPjteGr/4ypz2mjM5omlEizozXMopqyPgHwaL+3xTVlVPmcPL+3A5uu4bTp2LpzA4eTBl3xNCvnVY3qsxZ7ll+WUwgxNeRc5EIIISajbGDZFkn2lNnNygaWi2r8E5pJQNc1rjytkYDHQVNHjGjSwOzOidvUERvVhq989J8x9bnslHkclHnsaIBhKZq7Yj3f39i/t6OvA2TqHvf5txrsSSM6Oss/eNVRt8NGyjBHNcvfp5SzlF8WYlKT4FcIMaVNdGCZqxWNVWw4fxnL6wKEEgbNnTFCCYPj6gJFX6c62IypBtRXenHYdCylCMcNQgljzN/b9tYwHdE0C2v8lHscGFamDLJhKco9DhbW+GmPpEdVza33LP9gRjtbPdjgwKZr+Fx2Gqu8BONpfvl0E5Y1uqBdCDG+ZNmDEGLKywaWvYssjJSVYCL0zoU7nmtKh1oXXeFxsKi2jP0dUbpiBge74gS8zjF9b9n3qq/0UlvuJpo0SJsWDpuOz2XHshTNnbFRzc4Wa/nIZNg0KYTInQS/QohpYaICy3zls3msUIZbF13hcWCvziwb+eTpx3B8fWBM31v/9/L3e7+xrMHOzvLf9KctOecezsVk2DQphMidBL9CiGljIgLLyWCkGdMjkSTH1wV475vqxzxYKPbmvmLM8k+GTZNCiNxNmjW/nZ2drFu3jkAgQCAQYN26dXR1dQ35+HQ6zZe//GWOP/54fD4fdXV1XHHFFbS0tIxfo4UQYhIoxLpoy1JsPRRi4+52th4KDbn+dTzWYK9orOL7l53ELZedyE2XHM8tl53IrZedNOrlLZNh06QQIneTZuZ37dq1NDc388gjjwDw8Y9/nHXr1vHHP/5x0MfHYjFefPFF/u3f/o0TTzyRzs5OrrvuOi688EJeeOGF8Wy6EEKUvLHMmOabAmw81mAXcpa/WMsphBATY1IEv1u2bOGRRx7h2WefZdWqVQDceeedrF69mm3btrFkyZIBzwkEAjz++ON9brvttttYuXIl+/btY+7cuePSdiGEmCxGsy56tBXVJssa7KzJsmlSCDGySRH8PvPMMwQCgZ7AF+DUU08lEAjw9NNPDxr8DiYYDKJpGhUVFUM+JplMkkwme/4dCoWAzDKKdDq3zQzZx+X6eFE80helQ/qitAzXH8fM8MAMDwCmaWAOnjkMy1L86uk9xBIpFs7wdK/fVbhcOuVON/s749z79B6Om+UfMqjN9b1KwQl1Zfzne5azsy1CKJ7OpGabmflsY/m7lmOjdEhflI58+yKfPtNU/wVMJeib3/wmd911F9u3b+9z++LFi7nqqqtYv379iK+RSCR461vfytKlS/nVr3415ONuvPFGvva1rw24/b777sPr9ebfeCGEEEIIUVSxWIy1a9cSDAYpLx9+ydOEzvwOFWj29vzzzwMMyK0ImY0Gg93eXzqd5vLLL8eyLG6//fZhH7t+/Xquv/76nn+HQiEaGhpYs2bNiF9m7/d7/PHHOfvss3E4ZPfvRJK+KB3SF6WlEP3xwt4Ovv7HN5hT6cE2yLnYVIoDnXH+/YJjefM8WRYwFDk2Sof0RenIty+yV+pzMaHB7zXXXMPll18+7GPmzZvHK6+8wuHDhwfc19bWRm1t7bDPT6fTXHrppezZs4cnnnhixADW5XLhcg3M5ehwOPI+EEbzHFEc0helQ/qitIylPyrLPGg2O5GUwucaWFI4mjLQbHYqyzzS5zmQY6N0SF+Ujlz7Ip/+mtDgt7q6murq6hEft3r1aoLBIM899xwrV64EYOPGjQSDQU477bQhn5cNfHfs2MGTTz7JjBkzCtZ2IYSY7oqds1cIIYphUuT5XbZsGeeeey4f+9jHePbZZ3n22Wf52Mc+xrvf/e4+m92WLl3K73//ewAMw+B973sfL7zwAvfeey+maXLo0CEOHTpEKpWaqI8ihBBTxnjk7B1JrvmFhRAia1JkewC49957ufbaa1mzZg0AF154IT/60Y/6PGbbtm0Eg0EAmpub+cMf/gDASSed1OdxTz75JGeccUbR2yyEEFPdRKYAyze/sBBCwCQKfquqqobN0gD0qbwzb968AZV4hBBCFN5E5OwdbX5hIYSYNMGvEEKI0lXIimojsSzF3U830RVLM2+Gt2etsc9lx+u00dQR45dPN3FyQ2XJFs0QQkycSbHmVwghhMja3hpmZ2uEmjLXgHSXmqYx0+9iR2uE7a3hCWqhEKKUSfArhBBiUgnG0qQME7djYHo1ALfDRsowCcakSpcQYiAJfoUQQkwqAa8Dp91GIj14LeREOrP5LeCVPK1CiIEk+BVCCDGpZPMLt0WSAzY2Z/MLL6rxjzq/sKRPE2Jqkw1vQgghJpVsfuGb/rSFpo4YM/0u3I7MTHBbJDmm/MKSPk2IqU9mfoUQQpSUwWZe+992ckMlG85fxvK6AKGEQXNnjFDC4Li6wKjTnGXTp712IEi52059pZdyt70nfdqmpo4ifFohxHiTmV8hhBAlY7CZ1yqfE1B0RNMDZmO/f9lJBckvLOnThJg+JPgVQghREgYrXNEWTvD83syM68IaP/WV3qIUs8gnfdp45TMWQhSHLHsQQggx4frPvPpcdnQNjkRS2HSt+/9PousaPpedxiovwXiaXz7dVJANaZI+TYjpQ4JfIYQQE26wmddo0iSaMnDadFx2W+bfSQMofDELSZ8mxPQhwa8QQogJN9jMa9qysBTYNLDpGpZSpE2r5/5CzsYWO32aEKJ0SPArhBBiwmSzOOzriGEpiKeMnvscuo6uganAtBS6puGwHf3ZKuRsbDZ9WsDjoKkjRjRpYFqKaNKgqSM2pvRpQojSIhvehBBCTIjemR2ShsmRSJLD4QRLa8uo8DrxuWz4nHbCSQOlFOUeBz5X5mcrOxt7XF2gYLOxKxqr2HD+sp42HYkkcdptHFcX4ArJ8yvElCHBrxBCiHE3WGYHt8PGztYIr7WEWDjTx8wyN9V+J13xzLKGar8Ly1IFKWYxlBWNVZzcUFmQ9GlCiNIkwa8QQohxNVRO3Vnlblx2ne2HI+zvjJNIm7gcdlbOq0J15/lt7owVfTZW1zVJZybEFCbBrxBCiHE1XE7dSq+T5XXltEWSXH36MRxff3RZg8zGCiEKQYJfIYQQ4+poZgfXoPd7HDZ0YG6Vt88MrMzGCiEKQbI9CCGEGFeSU1cIMZEk+BVCCDGuJKeuEGIiSfArhBAFls1du3F3O1sPhQpSfncqkZy6QoiJJGt+hRCigHrnrk0Zmcv3C2v8XCl5YvuQnLpCiIkiwa8QQhTIYLlrE2mT11uC3PSnLWw4f5kEdb1ITl0hxESQ4FcIIQpgqNy1Ppcdr9NGU0eMXz7dxMkNlRLc9SI5dYUQ403W/AohRAEMl7tW0zRm+l3saI2wvTU8QS0UQggBEvwKIURBHM1daxv0frfDRsowCcbS49wyIYQQvUnwK4QQBSC5a4UQYnKQ4FcIIQpActdODEkrJ4TIl2x4E0KIAsjmrr3pT1to6ogx0+/C7cjMBLdFkpK7tggkrZwQYjRk5lcIIQokm7t2eV2AUMKguTNGKGFwXF1A0pwVWDat3GsHgpS77dRXeil323vSym1q6pjoJgohBHm5bgAAJHdJREFUSpTM/AohRAFJ7trik7RyQoixkOBXCCEKTHLXFlc+aeWkH4QQ/cmyByGEEJOKpJUTQoyFzPwKIYSYVHqnlfO5Bv6M9U8rZ1lKlqEIIXpI8CuEEGLSsCyFZSkqvQ6aOmIsmulD149exMymlTuuLsDimjLJCCGEGECCXyGEEJNC70A2GE/REU3RGUsxr8rLzDL3gLRym/d3ctOfttAVS1NT5sLtcJFImz0ZISQDhxDTkwS/QgghSl42tVk2kK0pc9EWSdLUHmP3kRhd8TQBj5Pj6gJccVojJzdUct39L0lGCCHEABL8CiGEKGlDpTabVe6mpszFztYIc6u8bHj3MpbWlqPrGlsPhSQjhBBiUJLtQQghREkbKrWZUopY0qTMZedgMAHQM4srGSGEEEOR4FcIIURJGyyQ7Yqleam5i5eau9jZFmF/R4z/ePhoZbfeGSEG0z8jhBBi+pDgVwghREnrH8g2d8Z5qbmTjmiapGGRMhVpS7GpqZP1D77KpqYOFteUsbDGT1skiVKqz+tlM0IsqvGzuKZsIj6SEGICSfArhBCipPUOZDuiCXa2hjGtgY9LGhZ7jkT5/l+2A3DlaY0EPJmUaNGkgWkpokmDpo5YT0YI2ewmxPQjwa8QQoiSpusaV57WiE3TeKU5hKkGPsaua+gamJbi5f1Bth4KsaKxig3nL2N5XYBQwqC5M0YoYXBcXUDSnAkxjUm2ByGEEJNC0rAGDXyzdE3DtBTxtMnrLSGOrQuworGKkxsqpcKbEKKHBL9CCCFKWjbVWdq0sGtgdAfA2fBVAaZS2LMBbb8AWdc1SWcmhOghyx6EEEKUtGyqs2q/C7utVynj7v/VAKUySx4AnA6d5XMk2BVCDE5mfoUQQpS0bKqzmZVeyj12UuEU2f1uvSd5LQW6Bic3VLK0duTg17KULIcQYhqS4FcIIURJy6Y6S6ZNGqp8RJIm8ZTZf3UDGjCnwsPnzl40YhC7qamDu59uYmdrhJSRyfm7sMbPlac1ykY4IaY4WfYghBCipPVOdRZw21k2u5wKr4Pe8a1dg9OOqeL7l580YvC6qamDm/60hdcOBCl326mv9FLutvN6S5Cb/nS0UIYQYmqS4FcIIURJy6Y6y+bsdegaJ9RXsHx2OTP9ThqrPHz7vSdwz7+cOmLgm9081xVLM2+GF5/Ljk3X8LnsNFZ5CcbT/PLpJixrmLQSQohJTYJfIYQQJW9Azt6OKNGUyeLaMj571iLe86b6nNbrZjfP1ZS50LS+j9c0jZl+FztaI2xvDRfrowghJpgEv0IIISaFFY1VfP+yk/jo2+YzK+ABDQ6FEvz3P/Zy3f0v5bRcIbt5zu2wDXq/22EjZZgEY+lCN18IUSIk+BVCCDFpbN7fya+ebeJgMEGN30VDnut1s5vnEmlz0PsT6czmt4DXUYzmCyFKgAS/QgghJoVCrNftvXlOqb6PU0rRFkmyqMbP4pqyYn8cIcQEkeBXCCHEpJDret1H3zjExt3tbD0UGhAI9988F00amJYimjRo6ogR8Di44rRGyfcrxBQmeX6FEEJMCkfX67oGvT9pWOzriPHtP2/FYdOGzN2b3TyXzfN7JJLEabdxXF2AKyTPrxBT3qSZ+e3s7GTdunUEAgECgQDr1q2jq6tr2OfceOONLF26FJ/PR2VlJWeddRYbN24cnwYLIYQoqOHW63bF02w/HCZlmAQ8Q+futSzF1kMhDFNx9ekLuPnSE7jpkuO55bITufWykXMECyEmv0kz87t27Vqam5t55JFHAPj4xz/OunXr+OMf/zjkcxYvXsyPfvQjFixYQDwe59Zbb2XNmjXs3LmTmTNnjlfThRBCFEB2ve7rLUG8TlvP0gcF7O+IkjItqrxOqv2ZZRE+lx2v00ZTRyyzFlgp7nlm36BV3ZbOGrkcshBiapgUM79btmzhkUce4b//+79ZvXo1q1ev5s477+Thhx9m27ZtQz5v7dq1nHXWWSxYsIDly5dzyy23EAqFeOWVV8ax9UIIIQphqPW6R8JJumIGLrtOfaW3z3rg7Frgl5u7+PeHXpeqbkKIyTHz+8wzzxAIBFi1alXPbaeeeiqBQICnn36aJUuWjPgaqVSKn/70pwQCAU488cQhH5dMJkkmkz3/DoVCAKTTadLp3PI+Zh+X6+NF8UhflA7pi9IyWfvjhLoy1p+7iPs27md3W5RgNIGpFGVOOGamj0qvDbD6PMfn1AjHkii3nSU1/u7gWOFy6ZQ73ezvjHPv03s4bpZ/Qja6Tda+mIqkL0pHvn2RT59pqn+ulxL0zW9+k7vuuovt27f3uX3x4sVcddVVrF+/fsjnPvzww1x++eXEYjFmz57NQw89xCmnnDLk42+88Ua+9rWvDbj9vvvuw+v1jv5DCCGEEEKIoojFYqxdu5ZgMEh5+fDLmCZ05neoQLO3559/HmBAWhvI5GQc7PbezjzzTF566SWOHDnCnXfeyaWXXsrGjRupqakZ9PHr16/n+uuv7/l3KBSioaGBNWvWjPhlZqXTaR5//HHOPvtsHA5JlD6RpC9Kh/RFaZlK/WFZiq88+CpbD4ZoqPT0+V1QSrG9NUI4keakhgrs+sDVfqZSHOiM8+8XHMub543/hrep1BeTnfRF6ci3L7JX6nMxocHvNddcw+WXXz7sY+bNm8crr7zC4cOHB9zX1tZGbW3tsM/3+XwsXLiQhQsXcuqpp7Jo0SJ+9rOfDTlb7HK5cLkGptFxOBx5HwijeY4oDumL0iF9UVqmSn986LT53PSnLezqSDDT78LtyGSFaIsk8bidoNuIpsHnGhj8RlMGms1OZZlnQr+LqdIXU4H0RenItS/y6a8JDX6rq6uprq4e8XGrV68mGAzy3HPPsXLlSgA2btxIMBjktNNOy+s9lVJ91vQKIYSY/IbL3fuhUxu559mmAVki4GhVt+PqAlLVTYhpYlJseFu2bBnnnnsuH/vYx7jjjjuATKqzd7/73X02uy1dupRvfetbXHLJJUSjUW666SYuvPBCZs+eTXt7O7fffjvNzc28//3vn6iPIoQQokhWNFZxckMl21vDBGNpAl4Hi2vK0HUNXYeb/rSFpo7YgJlhqeomxPQyKYJfgHvvvZdrr72WNWvWAHDhhRfyox/9qM9jtm3bRjAYBMBms7F161buvvtujhw5wowZMzjllFP4xz/+wfLly8e9/UIIIYpP17VBc/ZKVTchRNakCX6rqqr41a9+NexjeieucLvdPPjgg8VulhBCiEliuJlhIcT0MWmCXyGEEGKshpoZFkJMH5OiwpsQQgghhBCFIMGvEEIIIYSYNiT4FUIIIYQQ04YEv0IIIYQQYtqQ4FcIIYQQQkwbEvwKIYQQQohpQ4JfIYQQQggxbUieXyGEECIHlqWkQIYQU4AEv0IIIcQINjV19JRGThkmTruNhTV+rpTSyEJMOrLsQQghhBjGpqYObvrTFl47EKTcbae+0ku5287rLUFu+tMWNjV1THQThRB5kOBXCCGEGIJlKe5+uomuWJp5M7z4XHZsuobPZaexykswnuaXTzdhWWqimyqEyJEEv0IIIcQQtreG2dkaoabMhab1Xd+raRoz/S52tEbY3hqeoBYKIfIlwa8QQggxhGAsTcowcTtsg97vdthIGSbBWHqcWyaEGC0JfoUQQoghBLwOnHYbibQ56P2JdGbzW8DrGOeWCSFGS4JfIYQQYgiLa8pYWOOnLZJEqb7repVStEWSLKrxs7imbIJaKITIlwS/QgghxBB0XePK0xoJeBw0dcSIJg1MSxFNGjR1xAh4HFxxWqPk+xViEpHgVwghhBjGisYqNpy/jOV1AUIJg+bOGKGEwXF1ATacv0zy/AoxyUiRCyGEEGIEKxqrOLmhUiq8CTEFSPArhBBC5EDXNZbOKp/oZgghxkiWPQghhBBCiGlDZn6FEEKIArIsJcsjhChhEvwKIYQQBbKpqYO7n25iZ2uElJHJAbywxs+VpzXKxjghSoQsexBCCCEKYFNTBzf9aQuvHQhS7rZTX+ml3G3n9ZYgN/1pC5uaOia6iUIIJPgVQgghxsyyFHc/3URXLM28GV58Ljs2XcPnstNY5SUYT/PLp5uwLDXyiwkhikqCXyGEEGKMtreG2dkaoabMhab1Xd+raRoz/S52tEbY3hqeoBYKIbIk+BVCCCHGKBhLkzJM3A7boPe7HTZShkkwlh7nlgkh+pPgVwghhBijgNeB024jkTYHvT+Rzmx+C3gd49wyIUR/EvwKIYQQY7S4poyFNX7aIkmU6ruuVylFWyTJoho/i2vKJqiFQogsCX6FEEKIMdJ1jStPayTgcdDUESOaNDAtRTRp0NQRI+BxcMVpjZLvV4gSIMGvEEIIUQArGqtY/65lNFR6ORRKsKstQihhcFxdgA3nL5M8v0KUCClyIYQQQowgl6ptm5o6uOfZJg6HEpiWQtc0aspcfGj1XAl8hSghEvwKIYQQw8ilalu2wEVXLE1NmYvacjeJtMn+zhjf+vNWmfkVooTIsgchhBBiCLlUbZMCF0JMLhL8CiGEEIPINajdejgkBS6EmEQk+BVCCCEGkWvVttcPhKTAhRCTiAS/QgghxCByrdoGSIELISYRCX6FEEKIQeRatW15XbkUuBBiEpHgVwghhBhErlXbls4qlwIXQkwiEvwKIYQQg8inatuKxio2nL+M5XUBQgmD5s6YFLgQokRJnl8hhBBiCNmgNpvn90gkidNu47i6AFf0yvObfezJDZUjFsMQQkwsCX6FEEKIYeQT1Oq6xtJZ5RPQSiFEriT4FUIIIUYgQa0QU4es+RVCCCGEENOGBL9CCCGEEGLakOBXCCGEEEJMGxL8CiGEEEKIaUOCXyGEEEIIMW1I8CuEEEIIIaYNCX6FEEIIIcS0IcGvEEIIIYSYNiT4FUIIIYQQ04YEv0IIIYQQYtqQ4FcIIYQQQkwbEvwKIYQQQohpQ4JfIYQQQggxbdgnugGlTikFQCgUyvk56XSaWCxGKBTC4XAUq2kiB9IXpUP6orRIf5QO6YvSIX1ROvLti2yclo3bhiPB7wjC4TAADQ0NE9wSIYQQQggxnHA4TCAQGPYxmsolRJ7GLMuipaWFsrIyNE3L6TmhUIiGhgb2799PeXl5kVsohiN9UTqkL0qL9EfpkL4oHdIXpSPfvlBKEQ6HqaurQ9eHX9UrM78j0HWd+vr6UT23vLxcDp4SIX1ROqQvSov0R+mQvigd0helI5++GGnGN0s2vAkhhBBCiGlDgl8hhBBCCDFtSPBbBC6XixtuuAGXyzXRTZn2pC9Kh/RFaZH+KB3SF6VD+qJ0FLMvZMObEEIIIYSYNmTmVwghhBBCTBsS/AohhBBCiGlDgl8hhBBCCDFtSPArhBBCCCGmDQl+C6Czs5N169YRCAQIBAKsW7eOrq6uYZ9z4403snTpUnw+H5WVlZx11lls3LhxfBo8xeXbH+l0mi9/+cscf/zx+Hw+6urquOKKK2hpaRm/Rk9Rozk2HnzwQc455xyqq6vRNI2XXnppXNo61dx+++3Mnz8ft9vNihUr+Mc//jHs4//+97+zYsUK3G43CxYs4Cc/+ck4tXR6yKc/Dh48yNq1a1myZAm6rnPdddeNX0OngXz64sEHH+Tss89m5syZlJeXs3r1ah599NFxbO3Ulk9f/POf/+Qtb3kLM2bMwOPxsHTpUm699dZRva8EvwWwdu1aXnrpJR555BEeeeQRXnrpJdatWzfscxYvXsyPfvQjXn31Vf75z38yb9481qxZQ1tb2zi1eurKtz9isRgvvvgi//Zv/8aLL77Igw8+yPbt27nwwgvHsdVT02iOjWg0ylve8ha+/e1vj1Mrp57777+f6667jg0bNrB582be9ra38a53vYt9+/YN+vg9e/Zw3nnn8ba3vY3Nmzfz1a9+lWuvvZYHHnhgnFs+NeXbH8lkkpkzZ7JhwwZOPPHEcW7t1JZvXzz11FOcffbZ/PnPf2bTpk2ceeaZXHDBBWzevHmcWz715NsXPp+Pa665hqeeeootW7bwr//6r/zrv/4rP/3pT/N/cyXG5I033lCAevbZZ3tue+aZZxSgtm7dmvPrBINBBai//OUvxWjmtFGo/njuuecUoJqamorRzGlhrH2xZ88eBajNmzcXsZVT08qVK9XVV1/d57alS5eqr3zlK4M+/ktf+pJaunRpn9s+8YlPqFNPPbVobZxO8u2P3k4//XT12c9+tkgtm37G0hdZxx57rPra175W6KZNO4Xoi0suuUR96EMfyvu9ZeZ3jJ555hkCgQCrVq3que3UU08lEAjw9NNP5/QaqVSKn/70pwQCARnlj1Eh+gMgGAyiaRoVFRVFaOX0UKi+EPlJpVJs2rSJNWvW9Ll9zZo1Q37vzzzzzIDHn3POObzwwguk0+mitXU6GE1/iOIoRF9YlkU4HKaqqqoYTZw2CtEXmzdv5umnn+b000/P+/0l+B2jQ4cOUVNTM+D2mpoaDh06NOxzH374Yfx+P263m1tvvZXHH3+c6urqYjV1WhhLf2QlEgm+8pWvsHbtWsrLywvdxGmjEH0h8nfkyBFM06S2trbP7bW1tUN+74cOHRr08YZhcOTIkaK1dToYTX+I4ihEX3zve98jGo1y6aWXFqOJ08ZY+qK+vh6Xy8Wb3/xmPv3pT/PRj3407/eX4HcIN954I5qmDfvfCy+8AICmaQOer5Qa9PbezjzzTF566SWefvppzj33XC699FJaW1uL8nkmu/HoD8hsfrv88suxLIvbb7+94J9jKhivvhBj0/87Hul7H+zxg90uRiff/hDFM9q++PWvf82NN97I/fffP+jAXuRvNH3xj3/8gxdeeIGf/OQnfP/73+fXv/513u9rz/sZ08Q111zD5ZdfPuxj5s2bxyuvvMLhw4cH3NfW1jZgRNOfz+dj4cKFLFy4kFNPPZVFixbxs5/9jPXr14+p7VPRePRHOp3m0ksvZc+ePTzxxBMy6zuE8egLMXrV1dXYbLYBsyetra1Dfu+zZs0a9PF2u50ZM2YUra3TwWj6QxTHWPri/vvv51/+5V/43e9+x1lnnVXMZk4LY+mL+fPnA3D88cdz+PBhbrzxRj7wgQ/k9f4S/A6huro6pyUIq1evJhgM8txzz7Fy5UoANm7cSDAY5LTTTsvrPZVSJJPJUbV3qit2f2QD3x07dvDkk0/KD/4wJuLYELlzOp2sWLGCxx9/nEsuuaTn9scff5yLLrpo0OesXr2aP/7xj31ue+yxx3jzm9+Mw+EoanunutH0hyiO0fbFr3/9az7ykY/w61//mvPPP388mjrlFeq4GHXclPcWOTHAueeeq0444QT1zDPPqGeeeUYdf/zx6t3vfnefxyxZskQ9+OCDSimlIpGIWr9+vXrmmWfU3r171aZNm9S//Mu/KJfLpV577bWJ+AhTSr79kU6n1YUXXqjq6+vVSy+9pA4ePNjzXzKZnIiPMGXk2xdKKdXe3q42b96s/vSnPylA/eY3v1GbN29WBw8eHO/mT1q/+c1vlMPhUD/72c/UG2+8oa677jrl8/nU3r17lVJKfeUrX1Hr1q3refzu3buV1+tVn/vc59Qbb7yhfvaznymHw6H+53/+Z6I+wpSSb38opdTmzZvV5s2b1YoVK9TatWvV5s2b1euvvz4RzZ9S8u2L++67T9ntdvXjH/+4z29DV1fXRH2EKSPfvvjRj36k/vCHP6jt27er7du3q5///OeqvLxcbdiwIe/3luC3ANrb29UHP/hBVVZWpsrKytQHP/hB1dnZ2ecxgPrFL36hlFIqHo+rSy65RNXV1Smn06lmz56tLrzwQvXcc8+Nf+OnoHz7I5tSa7D/nnzyyXFv/1SSb18opdQvfvGLQfvihhtuGNe2T3Y//vGPVWNjo3I6nepNb3qT+vvf/95z35VXXqlOP/30Po//29/+pk4++WTldDrVvHnz1H/913+Nc4untnz7Y7BjoLGxcXwbPUXl0xenn376oH1x5ZVXjn/Dp6B8+uKHP/yhWr58ufJ6vaq8vFydfPLJ6vbbb1emaeb9vppS3bsahBBCCCGEmOIk24MQQgghhJg2JPgVQgghhBDThgS/QgghhBBi2pDgVwghhBBCTBsS/AohhBBCiGlDgl8hhBBCCDFtSPArhBBCCCGmDQl+hRBCjMqhQ4c4++yz8fl8VFRUjPv7a5rGQw89NO7vK4SY3CT4FUKUvA9/+MNomoamaTgcDhYsWMAXvvAFotFon8c98MADnHHGGQQCAfx+PyeccAJf//rX6ejoAODgwYOsXbuWJUuWoOs611133Yjv3d7ezrnnnktdXR0ul4uGhgauueYaQqHQsM/7xCc+wTHHHIPH42HmzJlcdNFFbN26tef+vXv38i//8i/Mnz8fj8fDMcccww033EAqlerzOtnP3fu/n/zkJ8O+9/XXX09VVRVz587lN7/5TZ/7fvvb33LBBReM+Llzceutt3Lw4EFeeukltm/fXpDXzMfBgwd517veNe7vK4SY3CT4FUJMCueeey4HDx5k9+7d/Md//Ae33347X/jCF3ru37BhA5dddhmnnHIK//d//8drr73G9773PV5++WXuueceAJLJJDNnzmTDhg2ceOKJOb2vrutcdNFF/OEPf2D79u3cdddd/OUvf+Hqq68e9nkrVqzgF7/4BVu2bOHRRx9FKcWaNWswTROArVu3YlkWd9xxB6+//jq33norP/nJT/jqV7864LV+8YtfcPDgwZ7/rrzyyiHf949//CP33Xcfjz32GN/5zne46qqraG9vB6Crq4sNGzbw4x//OKfPPpJdu3axYsUKFi1aRE1NTUFeMxfZAcKsWbNwuVzj9r5CiClizIWZhRCiyK688kp10UUX9bntox/9qJo1a5ZSSqmNGzcqQH3/+98f9PmdnZ0Dbjv99NPVZz/72VG15wc/+IGqr6/P6zkvv/yyAtTOnTuHfMx3v/tdNX/+/D63Aer3v/99zu/zne98R1122WU9/66pqVHPPfecUkqpj33sY+qWW27J+bVuv/12tWDBAuVwONTixYvVL3/5y577GhsbFdDz35VXXjng+Y888ohyuVwDvv/PfOYz6u1vf7tSSqkjR46oyy+/XM2ZM0d5PB513HHHqfvuu6/P408//XT16U9/Wn3uc59TM2bM6Hlu/+/mS1/6klq0aJHyeDxq/vz56l//9V9VKpXquf+GG25QJ554ovrlL3+pGhsbVXl5ubrssstUKBTqeYxpmurb3/62OuaYY5TT6VQNDQ3qP/7jP3rub25uVpdeeqmqqKhQVVVV6sILL1R79uzJ+TsVQkw8mfkVQkxKHo+HdDoNwL333ovf7+dTn/rUoI8t5HrUlpYWHnzwQU4//fScnxONRvnFL37B/PnzaWhoGPJxwWCQqqqqAbdfc801VFdXc8opp/CTn/wEy7KGfI0TTzyRF154gc7OTjZt2kQ8HmfhwoX885//5MUXX+Taa6/Nqc2///3v+exnP8vnP/95XnvtNT7xiU9w1VVX8eSTTwLw/PPPc+6553LppZdy8OBBfvCDHwx4jbPOOouKigoeeOCBnttM0+S3v/0tH/zgBwFIJBKsWLGChx9+mNdee42Pf/zjrFu3jo0bN/Z5rbvvvhu73c7/+3//jzvuuGPQNpeVlXHXXXfxxhtv8IMf/IA777yTW2+9tc9jdu3axUMPPcTDDz/Mww8/zN///ne+/e1v99y/fv16vvOd7/Bv//ZvvPHGG9x3333U1tYCEIvFOPPMM/H7/Tz11FP885//xO/3c+655w5YriKEKGETHX0LIcRI+s/8bty4Uc2YMUNdeumlSiml3vWud6kTTjghr9fMd+b38ssvVx6PRwHqggsuUPF4fMTn/PjHP1Y+n08BaunSpcPO+u7cuVOVl5erO++8s8/t3/jGN9TTTz+tNm/erG6++Wbl9XrVN77xjWHf94YbblDHHHOMOu6449SDDz6oksmkOu6449QLL7ygbrvtNrV48WJ12mmnqddee23I1zjttNPUxz72sT63vf/971fnnXdez78vuuiiQWd8e7v22mvVO97xjp5/P/roo8rpdKqOjo4hn3Peeeepz3/+8z3/Pv3009VJJ5004HGMMCv+3e9+V61YsaLn3zfccIPyer19Znq/+MUvqlWrVimllAqFQsrlcg3og6yf/exnasmSJcqyrJ7bksmk8ng86tFHHx2yHUKI0iIzv0KISeHhhx/G7/fjdrtZvXo1b3/727ntttsAUEqhaVpR3//WW2/lxRdf5KGHHmLXrl1cf/31Iz7ngx/8IJs3b+bvf/87ixYt4tJLLyWRSAx4XEtLC+eeey7vf//7+ehHP/r/27nfkCa3OA7g3+TOtvash7kcU4YT20KlTJYzx0wUo8igIYTVFnvRH6FXBbL5QgUnKoTZfFVR0CAQFMq9kBKiNGiJvQiFKAWtSJhpIyjxRSF27gtvw5l/Lxe89+77gTF2zs7vnOd5xvjt7Dwnrq6+vh52ux35+fmoqalBU1MT2tra1uy3sbERExMTeP36NSorK9Ha2orDhw9DoVCgubkZ4XAYFy5cgMfjWTXG6OgoHA5HXJnD4cDo6Oi6x72U2+3Gs2fPMDU1BWBxlr6iogJarRbA4kxwS0sL8vLyoNPpIEkSHj9+jMnJybg4BQUF6/Z1//59FBcXw2AwQJIkNDQ0/BYnMzMTGo0m9jotLQ2fP3+OHfOPHz9QXl6+YvxXr15hYmICGo0GkiRBkiSkpKTg+/fvePfu3cZPChFtqT+2egBERBtRVlaGmzdvQqFQID09HQqFIla3Z88ehMNhzM/Px5X/kwwGAwwGA7Kzs6HT6XDo0CE0NDQgLS1t1TayLEOWZVgsFhQVFUGr1SIUCuHMmTOx90xNTaGsrAx2ux23b99edxxFRUWYnZ3FzMxM7O/4tYyNjaGzsxPDw8O4e/cuSkpKkJqaiqqqKpw7dw6zs7PYuXPnim2X/6D4Oz8yCgsLsXv3bnR1deHSpUsIhUIIBoOx+vb2dgQCAXR0dGDfvn1Qq9W4cuXKb8sI1Gr1mv0MDQ3h9OnT8Pv9OHr0KGRZRldXF9rb2+Pet/zzsW3bttgyEpVKtWYfP3/+xIEDB9DZ2flbXWpq6pptiejfgzO/RPSfoFarYTabYTKZfktgXC4X5ubmcOPGjRXbfv369R8dixACwOLuEZttt7RNJBJBaWkprFYrgsEgkpLW/0oeHh6GUqnc0DpmIQSqq6vR3t4OSZKwsLAQWyf963m19cM5OTkIh8NxZYODg8jJyVm33+VcLhc6OzvR29uLpKQkHD9+PFb3/PlzOJ1OnD17Fvv370dWVhbGx8c33ceLFy9gMplQV1eHgoICWCwWfPz4cVMxLBYLVCoVnj59umK91WrF+Pg49Ho9zGZz3EOW5U2PmYi2Bmd+ieg/7+DBg/D5fKipqUEkEkFlZSXS09MxMTGBW7duobi4GJcvXwYAjIyMAADm5uYQjUYxMjKC5ORk5Obmrhj70aNHmJmZgc1mgyRJePv2LXw+HxwOBzIzMwEsJrHl5eW4d+8eCgsL8f79e3R3d+PIkSNITU1FJBLB1atXoVKpUFFRAWBxxre0tBQZGRm4du0aotForE+DwQBgcduy6elp2O12qFQqDAwMoK6uDtXV1Rva4uvOnTvQ6/U4ceIEgMVlC42NjRgaGkJfXx9yc3NXTaK9Xi+qqqpgtVpRXl6O3t5e9PT04MmTJ+v2u5zb7Ybf70dLSwtOnjwJpVIZqzObzXjw4AEGBweh1Wpx/fp1TE9PbzrJNpvNmJycRFdXF2w2Gx4+fIhQKLSpGEqlErW1tfD5fEhOTobD4UA0GsWbN29w/vx5uN1utLW1wel0oqmpCUajEZOTk+jp6YHX64XRaNxUf0S0RbZ0xTER0QastNXZSrq7u0VJSYnQaDRCrVaLvLw80dTUFLfVFpZsz/XrYTKZVo3Z398v7Ha7kGVZKJVKYbFYRG1tbVzMDx8+CABiYGBACCFEJBIRx44dE3q9XigUCmE0GoXL5RJjY2OxNsFgcMWxLP1a7uvrE/n5+UKSJLFjxw6xd+9e0dHRIebn59c9F9PT08JkMolIJBJX7vf7RUpKisjOzhYvX75cM8ZaW50JsbEb3n6x2WwCgOjv748r//Lli3A6nUKSJKHX60V9fb3weDxx13u1mxOx7IY3r9crdDqdkCRJnDp1SgQCASHLcqz+11ZnSwUCgbjrv7CwIJqbm4XJZBIKhUJkZGSI1tbWWP2nT5+Ex+MRu3btEtu3bxdZWVni4sWL4tu3bxs6D0S09bYJ8df/d0RERERE/3Nc80tERERECYPJLxERERElDCa/RERERJQwmPwSERERUcJg8ktERERECYPJLxERERElDCa/RERERJQwmPwSERERUcJg8ktERERECYPJLxERERElDCa/RERERJQwmPwSERERUcL4E89ALjwTGyDxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract the 'pos_neg' column from the metadata DataFrame\n",
    "clusters = meta_df['Group']\n",
    "color_palette = {'PSC': 'blue', 'HC': 'green'} \n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "# Plot each cluster separately\n",
    "for cluster in clusters.unique():\n",
    "    mask = (clusters == cluster)\n",
    "    plt.scatter(pcoa_df.loc[mask, 0], pcoa_df.loc[mask, 1], label=cluster, alpha=0.7)\n",
    "\n",
    "plt.xlabel(f\"PC1 {first_cmp:.3f} % of variance\")\n",
    "plt.ylabel(f\"PC2 {second_scmp:.3f} % of variance\")\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.savefig('./results/pca_plot_beta_stool.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}