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BMC Bioinformatics. 2016 Oct 10;17(1):420.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

Kim J1,2, Kim MS1,2, Koh AY2,3,4, Xie Y5,6,7, Zhan X8,9.

Author information

1
Department of Clinical Sciences, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.
2
Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.
3
Department of Pediatrics, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.
4
Department of Microbiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA.
5
Department of Clinical Sciences, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. Yang.Xie@utsouthwestern.edu.
6
Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. Yang.Xie@utsouthwestern.edu.
7
Department of Bioinformatics, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. Yang.Xie@utsouthwestern.edu.
8
Department of Clinical Sciences, Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. Xiaowei.Zhan@utsouthwestern.edu.
9
Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390, USA. Xiaowei.Zhan@utsouthwestern.edu.

Abstract

BACKGROUND:

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets.

RESULTS:

Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines.

CONCLUSION:

FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

PMID:
27724866
PMCID:
PMC5057277
DOI:
10.1186/s12859-016-1278-0
[Indexed for MEDLINE]
Free PMC Article

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