2015
DOI: 10.3389/fmicb.2015.01200
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Cross-biome comparison of microbial association networks

Abstract: Clinical and environmental meta-omics studies are accumulating an ever-growing amount of microbial abundance data over a wide range of ecosystems. With a sufficiently large sample number, these microbial communities can be explored by constructing and analyzing co-occurrence networks, which detect taxon associations from abundance data and can give insights into community structure. Here, we investigate how co-occurrence networks differ across biomes and which other factors influence their properties. For this… Show more

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Cited by 155 publications
(128 citation statements)
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“…Putative biotic interactions have been inferred from observational metagenomic studies, where positive or negative associations between microbial taxa are used as a proxy for positive or negative interactions (4951). This approach can be confounded by the structure of relative abundance data of most metagenomic studies and by shared niche preferences of noninteracting organisms (52).…”
Section: Discussionmentioning
confidence: 99%
“…Putative biotic interactions have been inferred from observational metagenomic studies, where positive or negative associations between microbial taxa are used as a proxy for positive or negative interactions (4951). This approach can be confounded by the structure of relative abundance data of most metagenomic studies and by shared niche preferences of noninteracting organisms (52).…”
Section: Discussionmentioning
confidence: 99%
“…6 Embeddedness of fungal OTUs with different distribution patterns in the communities in 1-year-old litter. Distributions of the network clustering coefficients are given for the OTUs of each distribution group according to Faust et al (2015). Colours code OTUs with distribution patterns as specified in Fig.…”
Section: Methodological Constraintsmentioning
confidence: 99%
“…To compare community structures between living and decaying leaves the dataset derived from 8 discs was used (Table S7). Network inference was adapted from Faust et al (2015), considering OTUs with a minimum occurrence in at least 3 samples from the respective plot. The obtained networks were visualized and processed as undirected networks in Cytoscape version 3.3.0 (Shannon et al 2003), with only positive edges being considered for the analyses.…”
Section: Statistical Analyses and Guild Delimitationmentioning
confidence: 99%
“…Host-associated microbiome networks (across several body sites and constructed with positive and negative interactions) showed higher connectedness (and network density) than soil networks (Faust et al 2015).…”
Section: Connectancementioning
confidence: 94%
“…Also, hostassociated networks contained more positive edges than soil microbial communities (Faust et al 2015;Friedman and Alm 2012) Invasion resistance arises in strongly interacting species-rich model competition communities (Case 1990) Transitive (hierarchical) competitive interactions are less stable than intransitive (cyclical) networks of competitive interactions (Petraitis 1979).…”
Section: Distribution Of Positive and Competitive Interactionsmentioning
confidence: 99%