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FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies
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-...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057277/ https://www.ncbi.nlm.nih.gov/pubmed/27724866 http://dx.doi.org/10.1186/s12859-016-1278-0 |
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author | Kim, Jiwoong Kim, Min Soo Koh, Andrew Y. Xie, Yang Zhan, Xiaowei |
author_facet | Kim, Jiwoong Kim, Min Soo Koh, Andrew Y. Xie, Yang Zhan, Xiaowei |
author_sort | Kim, Jiwoong |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1278-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5057277 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50572772016-10-20 FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies Kim, Jiwoong Kim, Min Soo Koh, Andrew Y. Xie, Yang Zhan, Xiaowei BMC Bioinformatics Software 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1278-0) contains supplementary material, which is available to authorized users. BioMed Central 2016-10-10 /pmc/articles/PMC5057277/ /pubmed/27724866 http://dx.doi.org/10.1186/s12859-016-1278-0 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Kim, Jiwoong Kim, Min Soo Koh, Andrew Y. Xie, Yang Zhan, Xiaowei FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title | FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title_full | FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title_fullStr | FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title_full_unstemmed | FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title_short | FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies |
title_sort | fmap: functional mapping and analysis pipeline for metagenomics and metatranscriptomics studies |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5057277/ https://www.ncbi.nlm.nih.gov/pubmed/27724866 http://dx.doi.org/10.1186/s12859-016-1278-0 |
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