Supporting data for "MGS-Fast: MetaGenomic Shotgun data Fast annotation using microbial gene catalogs"

Current methods used for annotating metagenomics shotgun sequencing (MGS) data, rely on a computationally intensive and low stringency approach of mapping each read to a generic database of proteins or reference microbial genomes. <br>We developed MGS-Fast, an alternative analysis approach for shotgun whole genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads, to the IGC database of well annotated genes compiled from human microbiome data. This method is rapid and provides high stringency matches (&gt;90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant KEGG gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image.