MetaDecoder

An algorithm for clustering metagenomic sequences [Modified by Josh L. Espinoza for Pyrodigal and PyHMMSearch support]

Cite MetaDecoder:

Liu, CC., Dong, SS., Chen, JB. et al. MetaDecoder: a novel method for clustering metagenomic contigs. Microbiome 10, 46 (2022). https://doi.org/10.1186/s40168-022-01237-8

Dependencies

• python (version >= 3.9)
• numpy
• scipy
• scikit-learn
• threadpoolctl
• pyrodigal
• pyhmmsearch

Installation

Download and install MetaDecoder (Do not clone this repository)

# Download and install MetaDecoder version 1.1.1rc2 #
pip install -U https://github.com/jolespin/metadecoder-nal/releases/download/1.1.1rc2/metadecoder-1.1.1rc2.tar.gz

The NewAtlantis Labs fork of MetaDecoder uses Pyrodigal and PyHMMSearch for predicting protein coding genes (if not proteins are provided) and mapping single-copy marker genes to contigs, respectively.

MetaDecoder has included the compiled FragGeneScan (version 1.31) and Hmmer (version 3.2.1).

The GPU version of MetaDecoder

MetaDecoder can be accelerated using the GPU on the basis of CUDA and CuPy.

To use the GPU version of Metadecoder, you need to have a compatible driver installed for your GPU (CUDA), and then install CuPy using pip3:

# You may need to install and upgrade setuptools and wheel using pip3 before. #
pip3 install --upgrade setuptools wheel
# Please note that XXX is the CUDA version. e.g. cupy-cuda101 means CuPy with CUDA 10.1. #
pip3 install cupy-cudaXXX

Please be careful not to install multiple CuPy packages at the same time.

MetaDecoder will automatically enable GPU if it is available.

And moreover, CuPy can use additional CUDA library (cuTENSOR) to accelerate tensor operations: UNTESTED

# Please note that XXX is the CUDA version. #
python3 -m cupyx.tools.install_library --cuda XXX --library cutensor
# Setting the environment variable to activate some CUDA features in CuPy. #
echo 'export CUPY_ACCELERATORS="cutensor"' >> ~/.bashrc

Usage

Preparations

Before running MetaDecoder, you may need to prepare some files by yourself.

• A FASTA formatted assembly file: ASSEMBLY.FASTA

• Some sorted BAM formatted read files with the SAME HEADER: SAMPLE1.BAM, SAMPLE2.BAM ...

Run MetaDecoder

Obtain the coverages of contigs

Input: SAMPLE1.BAM, SAMPLE2.BAM, ...

Output: METADECODER.COVERAGE

metadecoder coverage -b SAMPLE1.BAM ... SAMPLE2.BAM  -o METADECODER.COVERAGE

Map single-copy marker genes to the assembly

Input: ASSEMBLY.FASTA

Output: METADECODER.SEED

metadecoder seed --threads 4 -f ASSEMBLY.FASTA -o METADECODER.SEED

Run MetaDecoder algorithm to cluster contigs

Input: ASSEMBLY.FASTA, METADECODER.COVERAGE, METADECODER.SEED

Output: METADECODER.1.FASTA, METADECODER.2.FASTA, ...

metadecoder cluster -f ASSEMBLY.FASTA -c METADECODER.COVERAGE -s METADECODER.SEED -o METADECODER

Since v1.0.17, MetaDecoder can load multiple coverage files for clustering.

metadecoder cluster -f ASSEMBLY.FASTA -c *.METADECODER.COVERAGE -s METADECODER.SEED -o METADECODER

References

• Mina Rho, Haixu Tang, and Yuzhen Ye. FragGeneScan: Predicting Genes in Short and Error-prone Reads. Nucl. Acids Res., 2010 doi: 10.1093/nar/gkq747.

• nhmmer: DNA Homology Search With Profile HMMs. T. J. Wheeler, S. R. Eddy. Bioinformatics, 29:2487-2489, 2013.