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MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles

BACKGROUND: The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic sy...

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Autores principales: Shaw, Grace Tzun-Wen, Pao, Yueh-Yang, Wang, Daryi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124289/
https://www.ncbi.nlm.nih.gov/pubmed/27887570
http://dx.doi.org/10.1186/s12859-016-1359-0
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author Shaw, Grace Tzun-Wen
Pao, Yueh-Yang
Wang, Daryi
author_facet Shaw, Grace Tzun-Wen
Pao, Yueh-Yang
Wang, Daryi
author_sort Shaw, Grace Tzun-Wen
collection PubMed
description BACKGROUND: The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data. RESULTS: In this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles. MetaMIS first infers underlying microbial interactions from abundance tables for operational taxonomic units (OTUs) and then interprets interaction networks using the Lotka-Volterra model. We also embed a Bray-Curtis dissimilarity method in MetaMIS in order to evaluate the similarity to biological reality. MetaMIS is designed to tolerate a high level of missing data, and can estimate interaction information without the influence of rare microbes. For each interaction network, MetaMIS systematically examines interaction patterns (such as mutualism or competition) and refines the biotic role within microbes. As a case study, we collect a human male fecal microbiome and show that Micrococcaceae, a relatively low abundance OTU, is highly connected with 13 dominant OTUs and seems to play a critical role. MetaMIS is able to organize multiple interaction networks into a consensus network for comparative studies; thus we as a case study have also identified a consensus interaction network between female and male fecal microbiomes. CONCLUSIONS: MetaMIS provides an efficient and user-friendly platform that may reveal new insights into metagenomics data. MetaMIS is freely available at: https://sourceforge.net/projects/metamis/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1359-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-51242892016-12-08 MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles Shaw, Grace Tzun-Wen Pao, Yueh-Yang Wang, Daryi BMC Bioinformatics Software BACKGROUND: The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data. RESULTS: In this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles. MetaMIS first infers underlying microbial interactions from abundance tables for operational taxonomic units (OTUs) and then interprets interaction networks using the Lotka-Volterra model. We also embed a Bray-Curtis dissimilarity method in MetaMIS in order to evaluate the similarity to biological reality. MetaMIS is designed to tolerate a high level of missing data, and can estimate interaction information without the influence of rare microbes. For each interaction network, MetaMIS systematically examines interaction patterns (such as mutualism or competition) and refines the biotic role within microbes. As a case study, we collect a human male fecal microbiome and show that Micrococcaceae, a relatively low abundance OTU, is highly connected with 13 dominant OTUs and seems to play a critical role. MetaMIS is able to organize multiple interaction networks into a consensus network for comparative studies; thus we as a case study have also identified a consensus interaction network between female and male fecal microbiomes. CONCLUSIONS: MetaMIS provides an efficient and user-friendly platform that may reveal new insights into metagenomics data. MetaMIS is freely available at: https://sourceforge.net/projects/metamis/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1359-0) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-25 /pmc/articles/PMC5124289/ /pubmed/27887570 http://dx.doi.org/10.1186/s12859-016-1359-0 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
Shaw, Grace Tzun-Wen
Pao, Yueh-Yang
Wang, Daryi
MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title_full MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title_fullStr MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title_full_unstemmed MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title_short MetaMIS: a metagenomic microbial interaction simulator based on microbial community profiles
title_sort metamis: a metagenomic microbial interaction simulator based on microbial community profiles
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5124289/
https://www.ncbi.nlm.nih.gov/pubmed/27887570
http://dx.doi.org/10.1186/s12859-016-1359-0
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