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

• Published in: BMC bioinformatics Vol. 21; no. 1; pp. 1 - 8
• Main Authors: Kieser, Silas, Brown, Joseph, Zdobnov, Evgeny M., Trajkovski, Mirko, McCue, Lee Ann
• Format: Journal Article
• Language: English
• Published: London BioMed Central 22.06.2020; BioMed Central Ltd; Springer Nature B.V; BMC
• Subjects: Algorithms; Analysis; Analysis workflow; Annotation; Annotations; Assembly; Automation; BASIC BIOLOGICAL SCIENCES; Bioinformatics; Biomedical and Life Sciences; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Data processing; Gene mapping; Genes; Genomes; Genomics; High performance computing; Life Sciences; Mapping; Metagenome-assembled genomes; Metagenomics; Microarrays; Microorganisms; Nucleotide sequence; Phylogenetics; Quality control; Sequence analysis; Software; Source code; Taxonomy; Workflow; Workflow software; Analysis workflow; Metagenome-assembled genomes; Metagenomics; Annotation
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-020-03585-4

Background Metagenomics 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 data. Abundance estimates at genome resolution 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 data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas .