SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data

Silva, Genivaldo Gueiros Z.; Green, Kevin T.; Dutilh, Bas E.; Edwards, Robert A.

doi:10.1093/bioinformatics/btv584

Title: SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data

Journal Article · Fri Oct 09 00:00:00 EDT 2015 · Bioinformatics

DOI:https://doi.org/10.1093/bioinformatics/btv584· OSTI ID:1261146

Silva, Genivaldo Gueiros Z. ^[1]; Green, Kevin T. ^[2]; Dutilh, Bas E. ^[3]; Edwards, Robert A. ^[4]

San Diego State Univ. San Diego, CA (United States). Computational Science Research Center
San Diego State Univ. San Diego, CA (United States). Dept. of Biology
Univ. of Utrecht (Netherlands); Radboud Univ., Nijmegen (Netherlands); Federal Univ. of Rio de Janeiro (Brazil)
San Diego State Univ. San Diego, CA (United States). Computational Science Research Center; San Diego State Univ. San Diego, CA (United States). Dept. of Biology; Federal Univ. of Rio de Janeiro (Brazil); San Diego State Univ. San Diego, CA (United States). Dept. of of Computer Science; Argonne National Lab. (ANL), Argonne, IL (United States)

Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. We tested SUPER-FOCUS with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF)

Grant/Contract Number:: CNS-1305112; MCB-1330800; DUE-132809

OSTI ID:: 1261146

Journal Information:: Bioinformatics, Vol. 32, Issue 3; ISSN 1367-4803

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 93 works

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