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Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology
Mainstream studies of microbial community focused on critical organisms and their physiology. Recent advances in large-scale metagenome analysis projects initiated new researches in the complex correlations between large microbial communities. Specifically, previous studies focused on the nodes (i.e...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671402/ https://www.ncbi.nlm.nih.gov/pubmed/33575595 http://dx.doi.org/10.1093/nargab/lqaa042 |
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author | Yang, Pengshuo Tan, Chongyang Han, Maozhen Cheng, Lin Cui, Xuefeng Ning, Kang |
author_facet | Yang, Pengshuo Tan, Chongyang Han, Maozhen Cheng, Lin Cui, Xuefeng Ning, Kang |
author_sort | Yang, Pengshuo |
collection | PubMed |
description | Mainstream studies of microbial community focused on critical organisms and their physiology. Recent advances in large-scale metagenome analysis projects initiated new researches in the complex correlations between large microbial communities. Specifically, previous studies focused on the nodes (i.e. species) of the Species-Centric Networks (SCNs). However, little was understood about the change of correlation between network members (i.e. edges of the SCNs) when the network was disturbed. Here, we introduced a Correlation-Centric Network (CCN) to the microbial research based on the concept of edge networks. In CCN, each node represented a species–species correlation, and edge represented the species shared by two correlations. In this research, we investigated the CCNs and their corresponding SCNs on two large cohorts of microbiome. The results showed that CCNs not only retained the characteristics of SCNs, but also contained information that cannot be detected by SCNs. In addition, when the members of microbial communities were decreased (i.e. environmental disturbance), the CCNs fluctuated within a small range in terms of network connectivity. Therefore, by highlighting the important species correlations, CCNs could unveil new insights when studying not only the functions of target species, but also the stabilities of their residing microbial communities. |
format | Online Article Text |
id | pubmed-7671402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76714022021-02-10 Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology Yang, Pengshuo Tan, Chongyang Han, Maozhen Cheng, Lin Cui, Xuefeng Ning, Kang NAR Genom Bioinform Methods Article Mainstream studies of microbial community focused on critical organisms and their physiology. Recent advances in large-scale metagenome analysis projects initiated new researches in the complex correlations between large microbial communities. Specifically, previous studies focused on the nodes (i.e. species) of the Species-Centric Networks (SCNs). However, little was understood about the change of correlation between network members (i.e. edges of the SCNs) when the network was disturbed. Here, we introduced a Correlation-Centric Network (CCN) to the microbial research based on the concept of edge networks. In CCN, each node represented a species–species correlation, and edge represented the species shared by two correlations. In this research, we investigated the CCNs and their corresponding SCNs on two large cohorts of microbiome. The results showed that CCNs not only retained the characteristics of SCNs, but also contained information that cannot be detected by SCNs. In addition, when the members of microbial communities were decreased (i.e. environmental disturbance), the CCNs fluctuated within a small range in terms of network connectivity. Therefore, by highlighting the important species correlations, CCNs could unveil new insights when studying not only the functions of target species, but also the stabilities of their residing microbial communities. Oxford University Press 2020-06-25 /pmc/articles/PMC7671402/ /pubmed/33575595 http://dx.doi.org/10.1093/nargab/lqaa042 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Article Yang, Pengshuo Tan, Chongyang Han, Maozhen Cheng, Lin Cui, Xuefeng Ning, Kang Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title | Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title_full | Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title_fullStr | Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title_full_unstemmed | Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title_short | Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology |
title_sort | correlation-centric network (ccn) representation for microbial co-occurrence patterns: new insights for microbial ecology |
topic | Methods Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671402/ https://www.ncbi.nlm.nih.gov/pubmed/33575595 http://dx.doi.org/10.1093/nargab/lqaa042 |
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