Title |
FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies
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Published in |
BMC Bioinformatics, October 2016
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DOI | 10.1186/s12859-016-1278-0 |
Pubmed ID | |
Authors |
Jiwoong Kim, Min Soo Kim, Andrew Y. Koh, Yang Xie, Xiaowei Zhan |
Abstract |
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. 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. 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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India | 1 | 10% |
United States | 1 | 10% |
Austria | 1 | 10% |
Spain | 1 | 10% |
Unknown | 6 | 60% |
Demographic breakdown
Type | Count | As % |
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Scientists | 7 | 70% |
Members of the public | 2 | 20% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 1% |
Brazil | 3 | 1% |
South Africa | 1 | <1% |
Norway | 1 | <1% |
Canada | 1 | <1% |
United Kingdom | 1 | <1% |
Spain | 1 | <1% |
Belgium | 1 | <1% |
Unknown | 258 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 61 | 23% |
Researcher | 56 | 21% |
Student > Master | 40 | 15% |
Student > Bachelor | 21 | 8% |
Student > Doctoral Student | 18 | 7% |
Other | 38 | 14% |
Unknown | 37 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 80 | 30% |
Biochemistry, Genetics and Molecular Biology | 73 | 27% |
Computer Science | 20 | 7% |
Environmental Science | 16 | 6% |
Immunology and Microbiology | 6 | 2% |
Other | 30 | 11% |
Unknown | 46 | 17% |