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sc-multiome-analyze-wf.cwl
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sc-multiome-analyze-wf.cwl
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cwlVersion: v1.0
class: Workflow
requirements:
- class: SubworkflowFeatureRequirement
- class: StepInputExpressionRequirement
- class: InlineJavascriptRequirement
- class: MultipleInputFeatureRequirement
inputs:
feature_bc_matrices_folder:
type: File
doc: |
Path to the compressed folder with feature-barcode matrix from Cell Ranger ARC Count/Aggregate
experiment in MEX format. The rows consist of all the genes and peaks concatenated
together and the columns are restricted to those barcodes that are identified as cells.
aggregation_metadata:
type: File?
doc: |
Path to the metadata TSV/CSV file to set the datasets identities. If '--mex' points to
the Cell Ranger ARC Aggregate outputs, the aggr.csv file can be used. If input is not
provided, the default dummy_metadata.csv will be used instead.
atac_fragments_file:
type: File
secondaryFiles:
- .tbi
doc: |
Count and barcode information for every ATAC fragment observed in the experiment in TSV
format. Tbi-index file is required.
annotation_gtf_file:
type: File
doc: |
Path to the genome annotation file in GTF format.
grouping_data:
type: File?
doc: |
Path to the TSV/CSV file to define datasets grouping.
First column - 'library_id' with the values and order
that correspond to the 'library_id' column from the '
--identity' file, second column 'condition'.
Default: each dataset is assigned to its own group.
blacklist_regions_file:
type: File?
doc: |
Path to the optional BED file with the genomic blacklist regions.
barcodes_data:
type: File?
doc: |
Path to the TSV/CSV file to optionally prefilter and
extend Seurat object metadata be selected barcodes.
First column should be named as 'barcode'. If file
includes any other columns they will be added to the
Seurat object metadata ovewriting the existing ones if
those are present.
Default: all cells used, no extra metadata is added
rna_minimum_cells:
type: int?
doc: |
Include only genes detected in at least this many cells.
Default: 5 (applied to all datasets)
minimum_genes:
type:
- "null"
- int
- int[]
doc: |
Include cells where at least this many genes are detected. If multiple values
provided, each of them will be applied to the correspondent dataset from the
'--mex' input based on the '--identity' file.
Default: 250 (applied to all datasets)
maximum_genes:
type:
- "null"
- int
- int[]
doc: |
Include cells with the number of genes not bigger than this value. If multiple
values provided, each of them will be applied to the correspondent dataset from
the '--mex' input based on the '--identity' file.
Default: 5000 (applied to all datasets)
rna_minimum_umi:
type:
- "null"
- int
- int[]
doc: |
Include cells where at least this many UMI (RNA transcripts) are detected.
If multiple values provided, each of them will be applied to the correspondent
dataset from the '--mex' input based on the '--identity' file.
Default: 500 (applied to all datasets)
mito_pattern:
type: string?
doc: |
Regex pattern to identify mitochondrial genes.
Default: '^Mt-'
maximum_mito_perc:
type: float?
doc: |
Include cells with the percentage of transcripts mapped to mitochondrial
genes not bigger than this value.
Default: 5 (applied to all datasets)
minimum_novelty_score:
type:
- "null"
- float
- float[]
doc: |
Include cells with the novelty score not lower than this value, calculated for
as log10(genes)/log10(UMI) for RNA assay. If multiple values provided, each of them will
be applied to the correspondent dataset from the '--mex' input based on the
'--identity' file.
Default: 0.8 (applied to all datasets)
atac_minimum_cells:
type: int?
doc: |
Include only peaks detected in at least this many cells.
Default: 5 (applied to all datasets)
atac_minimum_umi:
type:
- "null"
- int
- int[]
doc: |
Include cells where at least this many UMI (ATAC transcripts) are detected.
If multiple values provided, each of them will be applied to the correspondent
dataset from the '--mex' input based on the '--identity' file.
Default: 1000 (applied to all datasets)
maximum_nucl_signal:
type:
- "null"
- float
- float[]
doc: |
Include cells with the nucleosome signal not bigger than this value.
Nucleosome signal quantifies the approximate ratio of mononucleosomal
to nucleosome-free fragments. If multiple values provided, each of
them will be applied to the correspondent dataset from the '--mex' input
based on the '--identity' file.
Default: 4 (applied to all datasets)
minimum_tss_enrich:
type:
- "null"
- float
- float[]
doc: |
Include cells with the TSS enrichment score not lower than this value.
Score is calculated based on the ratio of fragments centered at the TSS
to fragments in TSS-flanking regions. If multiple values provided, each
of them will be applied to the correspondent dataset from the '--mex' input
based on the '--identity' file.
Default: 2 (applied to all datasets)
minimum_frip:
type:
- "null"
- float
- float[]
doc: |
Include cells with the FRiP not lower than this value. If multiple values
provided, each of them will be applied to the correspondent dataset from the
'--mex' input based on the '--identity' file. FRiP is calculated for fragments.
Default: 0.15 (applied to all datasets)
maximum_blacklist_fraction:
type:
- "null"
- float
- float[]
doc: |
Include cells with the fraction of fragments in genomic blacklist regions
not bigger than this value. If multiple values provided, each of them
will be applied to the correspondent dataset from the '--mex' input based
on the '--identity' file.
Default: 0.05 (applied to all datasets)
cell_cycle_data:
type: File?
doc: |
Path to the TSV/CSV file with the information for cell cycle score assignment.
First column - 'phase', second column 'gene_id'. If loaded Seurat object already
includes cell cycle scores in 'S.Score' and 'G2M.Score' metatada columns they will
be removed.
Default: skip cell cycle score assignment.
highly_var_genes_count:
type: int?
doc: |
Number of highly variable genes used in datasets integration, scaling and
dimensionality reduction.
Default: 3000
regress_mito_perc:
type: boolean?
doc: |
Regress the percentage of transcripts mapped to mitochondrial genes as a
confounding source of variation.
Default: false
regress_cellcycle:
type: boolean?
doc: |
Regress cell cycle scores as a confounding source of variation.
Ignored if --cellcycle is not provided.
Default: false
rna_dimensions:
type:
- "null"
- int
- int[]
doc: |
Dimensionality from the 'pca' reduction to use when constructing weighted
nearest-neighbor graph before clustering (from 1 to 50). If single value N
is provided, use from 1 to N dimensions. If multiple values are provided,
subset to only selected dimensions.
Default: from 1 to 10
minimum_var_peaks_perc:
type: int?
doc: |
Minimum percentile for identifying the top most common peaks as highly variable.
For example, setting to 5 will use the the top 95 percent most common among all cells
peaks as highly variable. These peaks are used for datasets integration, scaling
and dimensionality reduction.
Default: 0 (use all available peaks)
atac_dimensions:
type:
- "null"
- int
- int[]
doc: |
Dimensionality from the 'atac_lsi' reduction to use when constructing weighted
nearest-neighbor graph before clustering (from 1 to 50). If single value N
is provided, use from 2 to N dimensions. If multiple values are provided,
subset to only selected dimensions.
Default: from 2 to 10
resolution:
type:
- "null"
- float
- float[]
doc: |
Clustering resolution applied to the constructed weighted nearest-neighbor
graph. Can be set as an array.
Default: 0.3, 0.5, 1.0
genes_of_interest:
type:
- "null"
- string
- string[]
doc: |
Genes of interest to build gene expression and Tn5 insertion frequency plots
for the nearest peaks. If '--fragments' is not provided only gene expression
plots will be built.
Default: None
rna_minimum_logfc:
type: float?
doc: |
For putative gene markers identification include only those genes that
on average have log fold change difference in expression between every
tested pair of clusters not lower than this value. Ignored if '--diffgenes'
is not set.
Default: 0.25
rna_minimum_pct:
type: float?
doc: |
For putative gene markers identification include only those genes that
are detected in not lower than this fraction of cells in either of the
two tested clusters. Ignored if '--diffgenes' is not set.
Default: 0.1
atac_minimum_logfc:
type: float?
doc: |
For differentially accessible peaks identification include only those peaks that
on average have log fold change difference in the chromatin accessibility between
every tested pair of clusters not lower than this value. Ignored if '--diffpeaks'
is not set.
Default: 0.25
atac_minimum_pct:
type: float?
doc: |
For differentially accessible peaks identification include only those peaks that
are detected in not lower than this fraction of cells in either of the two tested
clusters. Ignored if '--diffpeaks' is not set.
Default: 0.05
parallel_memory_limit:
type: int?
doc: |
Maximum memory in GB allowed to be shared between the workers
when using multiple --cpus.
Default: 32
vector_memory_limit:
type: int?
doc: |
Maximum vector memory in GB allowed to be used by R.
Default: 128
threads:
type: int?
doc: |
Number of cores/cpus to use.
Default: 1
outputs:
raw_1_2_qc_mtrcs_pca_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_1_2_qc_mtrcs_pca_plot_png
doc: |
PC1 and PC2 from the QC metrics PCA (not filtered).
PNG format
raw_2_3_qc_mtrcs_pca_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_2_3_qc_mtrcs_pca_plot_png
doc: |
PC2 and PC3 from the QC metrics PCA (not filtered).
PNG format
raw_cells_count_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_cells_count_plot_png
doc: |
Number of cells per dataset (not filtered).
PNG format
raw_rna_umi_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_rna_umi_dnst_plot_png
doc: |
UMI per cell density for RNA assay (not filtered).
PNG format
raw_gene_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_gene_dnst_plot_png
doc: |
Genes per cell density (not filtered).
PNG format
raw_gene_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_gene_umi_corr_plot_png
doc: |
Genes vs UMI per cell correlation for RNA assay (not filtered).
PNG format
raw_mito_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_mito_dnst_plot_png
doc: |
Percentage of transcripts mapped to mitochondrial genes per cell density (not filtered).
PNG format
raw_nvlt_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_nvlt_dnst_plot_png
doc: |
Novelty score per cell density for RNA assay (not filtered).
PNG format
raw_atac_umi_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_atac_umi_dnst_plot_png
doc: |
UMI per cell density for ATAC assay (not filtered).
PNG format
raw_peak_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_peak_dnst_plot_png
doc: |
Peaks per cell density (not filtered).
PNG format
raw_blck_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_blck_dnst_plot_png
doc: |
Fraction of ATAC fragments within genomic blacklist regions per cell density (not filtered).
PNG format
raw_rna_atac_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_rna_atac_umi_corr_plot_png
doc: |
UMI per cell correlation for RNA vs ATAC assays (not filtered).
PNG format
raw_tss_atac_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_tss_atac_umi_corr_plot_png
doc: |
TSS enrichment score vs UMI per cell correlation for ATAC assay (not filtered).
PNG format
raw_qc_mtrcs_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_qc_mtrcs_dnst_plot_png
doc: |
QC metrics per cell density (not filtered).
PNG format
raw_tss_nrch_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_tss_nrch_plot_png
doc: |
TSS enrichment score (not filtered).
PNG format
raw_frgm_hist_png:
type: File?
outputSource: sc_multiome_filter/raw_frgm_hist_png
doc: |
Fragments length histogram (not filtered).
PNG format
raw_rna_umi_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_rna_umi_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition UMI per cell density for RNA assay (not filtered).
PNG format
raw_gene_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_gene_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition genes per cell density (not filtered).
PNG format
raw_mito_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_mito_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the percentage of transcripts mapped
to mitochondrial genes per cell density (not filtered).
PNG format
raw_nvlt_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_nvlt_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the novelty score per cell density for RNA assay (not filtered).
PNG format
raw_atac_umi_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_atac_umi_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition UMI per cell density for ATAC assay (not filtered).
PNG format
raw_peak_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_peak_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition peaks per cell density (not filtered).
PNG format
raw_blck_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/raw_blck_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the fraction of ATAC fragments within genomic
blacklist regions per cell density (not filtered).
PNG format
fltr_1_2_qc_mtrcs_pca_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_1_2_qc_mtrcs_pca_plot_png
doc: |
PC1 and PC2 from the QC metrics PCA (filtered).
PNG format
fltr_2_3_qc_mtrcs_pca_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_2_3_qc_mtrcs_pca_plot_png
doc: |
PC2 and PC3 from the QC metrics PCA (filtered).
PNG format
fltr_cells_count_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_cells_count_plot_png
doc: |
Number of cells per dataset (filtered).
PNG format
fltr_rna_umi_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_rna_umi_dnst_plot_png
doc: |
UMI per cell density for RNA assay (filtered).
PNG format
fltr_gene_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_gene_dnst_plot_png
doc: |
Genes per cell density (filtered).
PNG format
fltr_gene_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_gene_umi_corr_plot_png
doc: |
Genes vs UMI per cell correlation for RNA assay (filtered).
PNG format
fltr_mito_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_mito_dnst_plot_png
doc: |
Percentage of transcripts mapped to mitochondrial genes per cell density (filtered).
PNG format
fltr_nvlt_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_nvlt_dnst_plot_png
doc: |
Novelty score per cell density for RNA assay (filtered).
PNG format
fltr_atac_umi_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_atac_umi_dnst_plot_png
doc: |
UMI per cell density for ATAC assay (filtered).
PNG format
fltr_peak_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_peak_dnst_plot_png
doc: |
Peaks per cell density (filtered).
PNG format
fltr_blck_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_blck_dnst_plot_png
doc: |
Fraction of ATAC fragments within genomic blacklist regions per cell density (filtered).
PNG format
fltr_rna_atac_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_rna_atac_umi_corr_plot_png
doc: |
UMI per cell correlation for RNA vs ATAC assays (filtered).
PNG format
fltr_tss_atac_umi_corr_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_tss_atac_umi_corr_plot_png
doc: |
TSS enrichment score vs UMI per cell correlation for ATAC assay (filtered).
PNG format
fltr_qc_mtrcs_dnst_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_qc_mtrcs_dnst_plot_png
doc: |
QC metrics per cell density (filtered).
PNG format
fltr_tss_nrch_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_tss_nrch_plot_png
doc: |
TSS enrichment score (filtered).
PNG format
fltr_frgm_hist_png:
type: File?
outputSource: sc_multiome_filter/fltr_frgm_hist_png
doc: |
Fragments length histogram (filtered).
PNG format
fltr_rna_umi_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_rna_umi_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition UMI per cell density for RNA assay (filtered).
PNG format
fltr_gene_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_gene_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition genes per cell density (filtered).
PNG format
fltr_mito_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_mito_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the percentage of transcripts mapped
to mitochondrial genes per cell density (filtered).
PNG format
fltr_nvlt_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_nvlt_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the novelty score per cell density for RNA assay (filtered).
PNG format
fltr_atac_umi_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_atac_umi_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition UMI per cell density for ATAC assay (filtered).
PNG format
fltr_peak_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_peak_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition peaks per cell density (filtered).
PNG format
fltr_blck_dnst_spl_cnd_plot_png:
type: File?
outputSource: sc_multiome_filter/fltr_blck_dnst_spl_cnd_plot_png
doc: |
Split by grouping condition the fraction of ATAC fragments within genomic
blacklist regions per cell density (filtered).
PNG format
sc_multiome_filter_stdout_log:
type: File
outputSource: sc_multiome_filter/stdout_log
doc: |
stdout log generated by sc_multiome_filter step
sc_multiome_filter_stderr_log:
type: File
outputSource: sc_multiome_filter/stderr_log
doc: |
stderr log generated by sc_multiome_filter step
rna_elbow_plot_png:
type: File?
outputSource: sc_rna_reduce/elbow_plot_png
doc: |
Elbow plot from cells PCA of RNA assay.
PNG format
rna_qc_dim_corr_plot_png:
type: File?
outputSource: sc_rna_reduce/qc_dim_corr_plot_png
doc: |
Correlation plots between QC metrics and cells PCA components
of RNA assay.
PNG format
rna_umap_qc_mtrcs_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_qc_mtrcs_plot_png
doc: |
QC metrics on cells UMAP for RNA assay.
PNG format
rna_umap_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_plot_png
doc: |
Cells UMAP for RNA assay.
PNG format
rna_umap_spl_ph_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_ph_plot_png
doc: |
Split by cell cycle phase cells UMAP for RNA assay.
PNG format
rna_umap_spl_mito_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_mito_plot_png
doc: |
Split by the percentage of transcripts mapped to mitochondrial
genes cells UMAP for RNA assay.
PNG format
rna_umap_spl_umi_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_umi_plot_png
doc: |
Split by the UMI per cell counts cells UMAP for RNA assay.
PNG format
rna_umap_spl_gene_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_gene_plot_png
doc: |
Split by the genes per cell counts cells UMAP for RNA assay.
PNG format
rna_umap_spl_idnt_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_idnt_plot_png
doc: |
Split by dataset cells UMAP for RNA assay.
PNG format
rna_umap_spl_cnd_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_spl_cnd_plot_png
doc: |
Split by grouping condition cells UMAP for RNA assay.
PNG format
rna_umap_gr_cnd_spl_ph_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_gr_cnd_spl_ph_plot_png
doc: |
Grouped by condition split by cell cycle cells UMAP for RNA assay.
PNG format
rna_umap_gr_cnd_spl_mito_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_gr_cnd_spl_mito_plot_png
doc: |
Grouped by condition split by the percentage of transcripts
mapped to mitochondrial genes cells UMAP for RNA assay.
PNG format
rna_umap_gr_cnd_spl_umi_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_gr_cnd_spl_umi_plot_png
doc: |
Grouped by condition split by the UMI per cell counts cells UMAP
for RNA assay.
PNG format
rna_umap_gr_cnd_spl_gene_plot_png:
type: File?
outputSource: sc_rna_reduce/umap_gr_cnd_spl_gene_plot_png
doc: |
Grouped by condition split by the genes per cell counts cells UMAP
for RNA assay.
PNG format
sc_rna_reduce_stdout_log:
type: File
outputSource: sc_rna_reduce/stdout_log
doc: |
stdout log generated by sc_rna_reduce step
sc_rna_reduce_stderr_log:
type: File
outputSource: sc_rna_reduce/stderr_log
doc: |
stderr log generated by sc_rna_reduce step
atac_qc_dim_corr_plot_png:
type: File?
outputSource: sc_atac_reduce/qc_dim_corr_plot_png
doc: |
Correlation plots between QC metrics and cells LSI dimensions
of ATAC assay.
PNG format
atac_umap_qc_mtrcs_plot_png:
type: File?
outputSource: sc_atac_reduce/umap_qc_mtrcs_plot_png
doc: |
QC metrics on cells UMAP for ATAC assay.
PNG format
atac_umap_plot_png:
type: File?
outputSource: sc_atac_reduce/umap_plot_png
doc: |
Cells UMAP for ATAC assay.
PNG format
atac_umap_spl_idnt_plot_png:
type: File?
outputSource: sc_atac_reduce/umap_spl_idnt_plot_png
doc: |
Split by dataset cells UMAP for ATAC assay.
PNG format
atac_umap_spl_cnd_plot_png:
type: File?
outputSource: sc_atac_reduce/umap_spl_cnd_plot_png
doc: |
Split by grouping condition cells UMAP for ATAC assay.
PNG format
sc_atac_reduce_stdout_log:
type: File
outputSource: sc_atac_reduce/stdout_log
doc: |
stdout log generated by sc_atac_reduce step
sc_atac_reduce_stderr_log:
type: File
outputSource: sc_atac_reduce/stderr_log
doc: |
stderr log generated by sc_atac_reduce step
wnn_umap_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/umap_res_plot_png
doc: |
Clustered cells UMAP for integrated ATAC and RNA assays.
PNG format
wnn_umap_spl_idnt_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/umap_spl_idnt_res_plot_png
doc: |
Split by dataset clustered cells UMAP for integrated
ATAC and RNA assays.
PNG format
wnn_cmp_gr_clst_spl_idnt_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_clst_spl_idnt_res_plot_png
doc: |
Grouped by cluster split by dataset cells composition plot for
integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_cmp_gr_idnt_spl_clst_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_idnt_spl_clst_res_plot_png
doc: |
Grouped by dataset split by cluster cells composition plot for
integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_umap_spl_cnd_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/umap_spl_cnd_res_plot_png
doc: |
Split by grouping condition clustered cells UMAP for
integrated ATAC and RNA assays.
PNG format
wnn_cmp_gr_clst_spl_cnd_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_clst_spl_cnd_res_plot_png
doc: |
Grouped by cluster split by condition cells composition plot for
integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_cmp_gr_cnd_spl_clst_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_cnd_spl_clst_res_plot_png
doc: |
Grouped by condition split by cluster cells composition plot for
integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_umap_spl_ph_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/umap_spl_ph_res_plot_png
doc: |
Split by cell cycle phase clustered cells UMAP for
integrated ATAC and RNA assays.
PNG format
wnn_cmp_gr_ph_spl_idnt_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_ph_spl_idnt_res_plot_png
doc: |
Grouped by cell cycle phase split by dataset cells composition plot
for integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_cmp_gr_ph_spl_clst_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cmp_gr_ph_spl_clst_res_plot_png
doc: |
Grouped by cell cycle phase split by cluster cells composition plot
for integrated ATAC and RNA assays. Downsampled.
PNG format
wnn_xpr_avg_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/xpr_avg_res_plot_png
doc: |
Log normalized scaled average gene expression per cluster for
integrated ATAC and RNA assays.
PNG format
wnn_xpr_per_cell_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/xpr_per_cell_res_plot_png
doc: |
Log normalized gene expression on cells UMAP for integrated
ATAC and RNA assays.
PNG format
wnn_xpr_per_cell_sgnl_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/xpr_per_cell_sgnl_res_plot_png
doc: |
Log normalized gene expression density on cells UMAP.
PNG format
wnn_xpr_dnst_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/xpr_dnst_res_plot_png
doc: |
Log normalized gene expression density per cluster for
integrated ATAC and RNA assays.
PNG format
wnn_cvrg_res_plot_png:
type:
- "null"
- type: array
items: File
outputSource: sc_wnn_cluster/cvrg_res_plot_png
doc: |
Tn5 insertion frequency plot around gene for integrated
ATAC and RNA assays.
PNG format
gene_markers_tsv: