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Cao Y, Zheng X, Li F, et al. mmnet: An R Package for Metagenomics Systems Biology Analysis. Biomed Res Int. 2015;2015:167249doi: 10.1155/2015/167249.
Cao, Y., Zheng, X., Li, F., & Bo, X. (2015). mmnet: An R Package for Metagenomics Systems Biology Analysis. BioMed research international, 2015167249. https://doi.org/10.1155/2015/167249
Cao, Yang, et al. "mmnet: An R Package for Metagenomics Systems Biology Analysis." BioMed research international vol. 2015 (2015): 167249. doi: https://doi.org/10.1155/2015/167249
Cao Y, Zheng X, Li F, Bo X. mmnet: An R Package for Metagenomics Systems Biology Analysis. Biomed Res Int. 2015;2015:167249. doi: 10.1155/2015/167249. Epub 2015 Sep 03. PMID: 26421278; PMCID: PMC4573221.
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Biomed Res Int. 2015;2015:167249. doi: 10.1155/2015/167249. Epub 2015 Sep 03.

mmnet: An R Package for Metagenomics Systems Biology Analysis.

BioMed research international

Yang Cao, Xiaofei Zheng, Fei Li, Xiaochen Bo

Affiliations

  1. Department of Biotechnology, Beijing Institute of Radiation Medicine, 27 Taiping Road, Haidian District, Beijing 100850, China.
  2. Department of Biochemistry and Molecular Biology, Beijing Institute of Radical Medicine, 27 Taiping Road, Haidian District, Beijing 100850, China.

PMID: 26421278 PMCID: PMC4573221 DOI: 10.1155/2015/167249

Abstract

The human microbiome plays important roles in human health and disease. Previous microbiome studies focused mainly on single pure species function and overlooked the interactions in the complex communities on system-level. A metagenomic approach introduced recently integrates metagenomic data with community-level metabolic network modeling, but no comprehensive tool was available for such kind of approaches. To facilitate these kinds of studies, we developed an R package, mmnet, to implement community-level metabolic network reconstruction. The package also implements a set of functions for automatic analysis pipeline construction including functional annotation of metagenomic reads, abundance estimation of enzymatic genes, community-level metabolic network reconstruction, and integrated network analysis. The result can be represented in an intuitive way and sent to Cytoscape for further exploration. The package has substantial potentials in metagenomic studies that focus on identifying system-level variations of human microbiome associated with disease.

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