ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

Kieser, Silas; Brown, Joseph; Zdobnov, Evgeny M.; Trajkovski, Mirko; McCue, Lee Ann

doi:10.1186/s12859-020-03585-4

Title: ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

Journal Article · Mon Jun 22 00:00:00 EDT 2020 · BMC Bioinformatics

DOI:https://doi.org/10.1186/s12859-020-03585-4· OSTI ID:1646625

Kieser, Silas ^[1]; Brown, Joseph ^[2]; Zdobnov, Evgeny M. ^[3]; Trajkovski, Mirko ^[4];

^[5]

Swiss Inst. of Bioformatics, Lausanne (Switzerland); Centre Medical Universitaire, Geneva (Switzerland)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Utah, Salt Lake City, UT (United States)
Swiss Inst. of Bioformatics, Lausanne (Switzerland); Univ. of Geneva (Switzerland)
Centre Medical Universitaire, Geneva (Switzerland); Univ. of Geneva (Switzerland)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Background: Metagenomics and metatranscriptomics studies provide valuable insight into the composition and function of microbial populations from diverse environments, however the data processing pipelines that rely on mapping reads to gene catalogs or genome databases for cultured strains yield results that underrepresent the genes and functional potential of uncultured microbes. Recent improvements in sequence assembly methods have eased the reliance on genome databases, thereby allowing the recovery of genomes from uncultured microbes. However, configuring these tools, linking them with advanced binning and annotation tools, and maintaining provenance of the processing continues to be challenging for researchers. Results: Here we present ATLAS, a software package for customizable data processing from raw sequence reads to functional and taxonomic annotations using state-of-the-art tools to assemble, annotate, quantify, and bin metagenome and metatranscriptome data. Genome-centric resolution and abundance estimates are provided for each sample in a dataset. ATLAS is written in Python and the workflow implemented in Snakemake; it operates in a Linux environment, and is compatible with Python 3.5+ and Anaconda 3+ versions. The source code for ATLAS is freely available, distributed under a BSD-3 license. Conclusions: ATLAS provides a user-friendly, modular and customizable Snakemake workflow for metagenome and metatranscriptome data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1646625

Report Number(s):: PNNL-SA-143152

Journal Information:: BMC Bioinformatics, Vol. 21, Issue 1; ISSN 1471-2105

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 46 works

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