Update README.md

README.md

@@ -1,10 +1,9 @@
 # PLASS and PenguiN assembler
 [![BioConda Install](https://img.shields.io/conda/dn/bioconda/plass.svg?style=flag&label=BioConda%20install)](https://anaconda.org/bioconda/plass)
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-[![Build Status](https://travis-ci.org/soedinglab/plass.svg?branch=master)](https://travis-ci.org/soedinglab/plass)
 [![DOI](https://zenodo.org/badge/118119513.svg)](https://zenodo.org/badge/latestdoi/118119513)
 
-Plass (Protein-Level ASSembler) is a software to assemble protein sequences from short read sequencing data, while PenguiN (Protein guided nucleotide assembler) assembles DNA/RNA contigs. Both are build to assemble data from complex metagenomic datasets. This software is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS and is designed to run on multiple cores. 
+Plass (Protein-Level ASSembler) and PenguiN (Protein guided nucleotide assembler) are software to assemble protein sequences or DNA/RNA contigs from short read sequencing data meant to work best for complex metagenomic or metatranscriptomic datasets. Plass and Penguin are GPL-licensed open source software implemented in C++ and available for Linux and macOS and are designed to run on multiple cores. 
 
 [Plass:](https://github.com/soedinglab/plass/tree/master?tab=readme-ov-file#plass---protein-level-assembler) [Steinegger M, Mirdita M and Soeding J. Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold. Nature Methods, doi: doi.org/10.1038/s41592-019-0437-4 (2019)](https://www.nature.com/articles/s41592-019-0437-4).
 
@@ -18,21 +17,24 @@ Each catalog is a single FASTA file containing the sequences, the header identif
 The catalogues can be downloaded [here](http://wwwuser.gwdg.de/~compbiol/plass/current_release/).
 We provide a [HH-suite3](https://github.com/soedinglab/hh-suite) database called "BFD" containing sequences from the Metaclust, SRC, MERC and Uniport at [here](https://bfd.mmseqs.com/).
 
-# PenguiN - Protein-guided Nucleotide Assembler
-PenguiN a software to assemble short read sequencing data on a nucleotide level. In a first step it assembles coding sequences using the information from the translated protein sequences. In a second step it links them across non-coding regions. The main purpose of PenguiN is the assembly of complex metagenomic and metatranscriptomic datasets. It was especially tested for the assembly of viral genomes as well as 16S rRNA gene seqeunces. It assembles 3-40 times more complete viral genomes and 6 times as many 16S rRNA sequences than state of the art assemblers like Megahit and the SPAdes variants. PenguiN is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores. 
+# PenguiN - Protein-guided Nucleotide assembler
+PenguiN a software to assemble short read sequencing data on a nucleotide level. In a first step it assembles coding sequences using the information from the translated protein sequences. In a second step it links them across non-coding regions. The main purpose of PenguiN is the assembly of complex metagenomic and metatranscriptomic datasets. It was especially tested for the assembly of viral genomes as well as 16S rRNA gene seqeunces. It assembles 3-40 times more complete viral genomes and six times as many 16S rRNA sequences than state of the art assemblers like Megahit and the SPAdes variants.
 
 ### Install Plass and PenguiN
-Our sofwtare can be install via [conda](https://github.com/conda/conda) or as statically compiled Linux version. It requires a 64-bit Linux/MacOS system (check with `uname -a | grep x86_64`) with at least the SSE2 instruction set.
+Our software can be install via [conda](https://github.com/conda-forge/miniforge) or as statically compiled binaries. It requires a 64-bit Linux or macOS system.
 
      # install from bioconda
      conda install -c conda-forge -c bioconda plass 
+     # install docker
+     docker pull ghcr.io/soedinglab/plass:latest
      # static build with AVX2 (fastest)
      wget https://mmseqs.com/plass/plass-linux-avx2.tar.gz; tar xvfz plass-linux-avx2.tar.gz; export PATH=$(pwd)/plass/bin/:$PATH
      # static build with SSE4.1
      wget https://mmseqs.com/plass/plass-linux-sse41.tar.gz; tar xvfz plass-linux-sse41.tar.gz; export PATH=$(pwd)/plass/bin/:$PATH
-     # static build with SSE2 (slowest, for very old systems)
-     wget https://mmseqs.com/plass/plass-linux-sse2.tar.gz; tar xvfz plass-linux-sse2.tar.gz; export PATH=$(pwd)/plass/bin/:$PATH
-
+     # universal build with macOS (Intel or Apple Silicon)
+     wget https://mmseqs.com/plass/plass-osx-universal.tar.gz; tar xvfz plass-osx-universal.tar.gz; export PATH=$(pwd)/plass/bin/:$PATH
+
+Other precompiled binaries for SSE2, ARM and PowerPC can be found at [mmseqs.com/plass](https://mmseqs.com/plass).
 
 ## How to assemble
 Plass and PenguiN can assemble both paired-end reads (FASTQ) and single reads (FASTA or FASTQ):
@@ -55,24 +57,24 @@ Important parameters:
      --num-iterations     Number of iterations of assembly
      --filter-proteins    Switches the neural network protein filter off/on
 
-Plass Modules: 
+Plass workflows: 
 
       plass assemble      Assembles proteins (i:Nucleotides -> o:Proteins)
       
       
-PenguiN Modules: 
+PenguiN workflows: 
 
       penguin guided_nuclassemble  Assembles nucleotides using protein and nucleotide information (i:Nucleotides -> o:Nucleotides)
       penguin nuclassemble         Assembles nucleotides using only nucleotdie information (i:Nucleotides -> o:Nucleotides)
 
 ### Assemble using MPI 
-Both tools can be distributed over several homogeneous computers. However the TMP folder has to be shared between all nodes (e.g. NFS). The following command assembles several nodes:
+Both tools can be distributed over several homogeneous computers. However the `tmp` folder has to be shared between all nodes (e.g. NFS). The following command assembles on several nodes:
 
     RUNNER="mpirun -np 42" plass assemble examples/reads_1.fastq.gz examples/reads_2.fastq.gz assembly.fas tmp
 
 
 ### Compile from source
-Compiling from source has the advantage that it will be optimized to the specific system, which should improve its performance. To compile `git`, `g++` (4.6 or higher) and `cmake` (3.0 or higher) are required. Afterwards, the PLASS and PenguiN binaries will be located in the `build/bin` directory.
+Compiling from source has the advantage that it will be optimized to the specific system, which should improve its performance. To compile `git`, `g++` (4.9 or higher) and `cmake` (3.0 or higher) are required. Afterwards, the PLASS and PenguiN binaries will be located in the `build/bin` directory.
 
       git clone https://github.com/soedinglab/plass.git
       cd plass
@@ -84,17 +86,16 @@ Compiling from source has the advantage that it will be optimized to the specifi
         
 :exclamation: If you want to compile PLASS or PenguiN on macOS, please install and use `gcc` from Homebrew. The default macOS `clang` compiler does not support OpenMP and PLASS will not be able to run multithreaded. Use the following cmake call:
 
-      CXX="$(brew --prefix)/bin/g++-8" cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=. ..
+      CXX="$(brew --prefix)/bin/g++-13" cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=. ..
 
 #### Dependencies
 
-When compiling from source, our sofwtare requires `zlib` and `bzip`.
+When compiling from source, our sofwtare requires the `zlib` and `bzip` installed.
 
 ### Use the docker image
 We also provide a Docker image of Plass. You can mount the current directory containing the reads to be assembled and run plass with the following command:
 
-      docker pull soedinglab/plass
-      docker run -ti --rm -v "$(pwd):/app" -w /app plass assemble reads_1.fastq reads_2.fastq assembly.fas tmp
+      docker run -ti --rm -v "$(pwd):/app" -w /app ghcr.io/soedinglab/plass:latest assemble reads_1.fastq reads_2.fastq assembly.fas tmp
 
 ## Hardware requirements
 Plass needs roughly 1 byte of memory per residue to work efficiently. Plass will scale its memory consumption based on the available main memory of the machine. Plass needs a CPU with at least the SSE4.1 instruction set to run.