| Literature DB >> 30298259 |
Mehdi Layeghifard1, David M Hwang2,3, David S Guttman4,5.
Abstract
Microbiomes are complex microbial communities whose structure and function are heavily influenced by microbe-microbe and microbe-host interactions mediated by a range of mechanisms, all of which have been implicated in the modulation of disease progression and clinical outcome. Therefore, understanding the microbiome as a whole, including both the complex interplay among microbial taxa and interactions with their hosts, is essential for understanding the spectrum of roles played by microbiomes in host health, development, dysbiosis, and polymicrobial infections. Network theory, in the form of systems-oriented, graph-theoretical approaches, is an exciting holistic methodology that can facilitate microbiome analysis and enhance our understanding of the complex ecological and evolutionary processes involved. Using network theory, one can model and analyze a microbiome and all its complex interactions in a single network. Here, we describe in detail and step by step, the process of building, analyzing and visualizing microbiome networks from operational taxonomic unit (OTU) tables in R and RStudio, using several different approaches and extensively commented code snippets.Entities:
Keywords: Graph theory; Microbial co-occurrence; Microbiome; Network; OTU table; R; RStudio; igraph
Mesh:
Year: 2018 PMID: 30298259 DOI: 10.1007/978-1-4939-8728-3_16
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745