Unknown

Dataset Information

0

Inferring directional relationships in microbial communities using signed Bayesian networks.


ABSTRACT:

Background

Microbe-microbe and host-microbe interactions in a microbiome play a vital role in both health and disease. However, the structure of the microbial community and the colonization patterns are highly complex to infer even under controlled wet laboratory conditions. In this study, we investigate what information, if any, can be provided by a Bayesian Network (BN) about a microbial community. Unlike the previously proposed Co-occurrence Networks (CoNs), BNs are based on conditional dependencies and can help in revealing complex associations.

Results

In this paper, we propose a way of combining a BN and a CoN to construct a signed Bayesian Network (sBN). We report a surprising association between directed edges in signed BNs and known colonization orders.

Conclusions

BNs are powerful tools for community analysis and extracting influences and colonization patterns, even though the analysis only uses an abundance matrix with no temporal information. We conclude that directed edges in sBNs when combined with negative correlations are consistent with and strongly suggestive of colonization order.

SUBMITTER: Sazal M 

PROVIDER: S-EPMC7751116 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

altmetric image

Publications

Inferring directional relationships in microbial communities using signed Bayesian networks.

Sazal Musfiqur M   Mathee Kalai K   Ruiz-Perez Daniel D   Cickovski Trevor T   Narasimhan Giri G  

BMC genomics 20201221 Suppl 6


<h4>Background</h4>Microbe-microbe and host-microbe interactions in a microbiome play a vital role in both health and disease. However, the structure of the microbial community and the colonization patterns are highly complex to infer even under controlled wet laboratory conditions. In this study, we investigate what information, if any, can be provided by a Bayesian Network (BN) about a microbial community. Unlike the previously proposed Co-occurrence Networks (CoNs), BNs are based on condition  ...[more]

Similar Datasets

| S-EPMC5760079 | biostudies-literature
| S-EPMC5648141 | biostudies-literature
| S-EPMC8557847 | biostudies-literature
| S-EPMC4237410 | biostudies-literature
| S-EPMC4833320 | biostudies-literature
| S-EPMC7613200 | biostudies-literature
2014-12-21 | GSE64376 | GEO
| S-EPMC4126456 | biostudies-literature
| S-EPMC4096371 | biostudies-literature
| S-EPMC5804367 | biostudies-literature