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ABSTRACT: Background
Whole-genome "shotgun" (WGS) metagenomic sequencing is an increasingly widely used tool for analyzing the metagenomic content of microbiome samples. While WGS data contains gene-level information, it can be challenging to analyze the millions of microbial genes which are typically found in microbiome experiments. To mitigate the ultrahigh dimensionality challenge of gene-level metagenomics, it has been proposed to cluster genes by co-abundance to form Co-Abundant Gene groups (CAGs). However, exhaustive co-abundance clustering of millions of microbial genes across thousands of biological samples has previously been intractable purely due to the computational challenge of performing trillions of pairwise comparisons.Results
Here we present a novel computational app
SUBMITTER: Minot SS
PROVIDER: S-EPMC6670193 | biostudies-literature | 2019 Aug
REPOSITORIES: biostudies-literature