TY - JOUR
T1 - MetaModules identifies key functional subnetworks in microbiome-related disease
AU - May, Ali
AU - Brandt, Bernd W.
AU - El-Kebir, Mohammed
AU - Klau, Gunnar W.
AU - Zaura, Egija
AU - Crielaard, Wim
AU - Heringa, Jaap
AU - Abeln, Sanne
N1 - Publisher Copyright:
© 2015 The Author 2015. Published by Oxford University Press. All rights reserved.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - Motivation: The human microbiome plays a key role in health and disease. Thanks to comparative metatranscriptomics, the cellular functions that are deregulated by the microbiome in disease can now be computationally explored. Unlike gene-centric approaches, pathway-based methods provide a systemic view of such functions; however, they typically consider each pathway in isolation and in its entirety. They can therefore overlook the key differences that (i) span multiple pathways, (ii) contain bidirectionally deregulated components, (iii) are confined to a pathway region. To capture these properties, computational methods that reach beyond the scope of predefined pathways are needed. Results: By integrating an existing module discovery algorithm into comparative metatranscriptomic analysis, we developed metaModules, a novel computational framework for automated identification of the key functional differences between health- and disease-associated communities. Using this framework, we recovered significantly deregulated subnetworks that were indeed recognized to be involved in two well-studied, microbiome-mediated oral diseases, such as butanoate production in periodontal disease and metabolism of sugar alcohols in dental caries. More importantly, our results indicate that our method can be used for hypothesis generation based on automated discovery of novel, disease-related functional subnetworks, which would otherwise require extensive and laborious manual assessment. Availability and implementation: metaModules is available at https://bitbucket.org/alimay/metamodules/ Supplementary information: Supplementary data are available at Bioinformatics online.
AB - Motivation: The human microbiome plays a key role in health and disease. Thanks to comparative metatranscriptomics, the cellular functions that are deregulated by the microbiome in disease can now be computationally explored. Unlike gene-centric approaches, pathway-based methods provide a systemic view of such functions; however, they typically consider each pathway in isolation and in its entirety. They can therefore overlook the key differences that (i) span multiple pathways, (ii) contain bidirectionally deregulated components, (iii) are confined to a pathway region. To capture these properties, computational methods that reach beyond the scope of predefined pathways are needed. Results: By integrating an existing module discovery algorithm into comparative metatranscriptomic analysis, we developed metaModules, a novel computational framework for automated identification of the key functional differences between health- and disease-associated communities. Using this framework, we recovered significantly deregulated subnetworks that were indeed recognized to be involved in two well-studied, microbiome-mediated oral diseases, such as butanoate production in periodontal disease and metabolism of sugar alcohols in dental caries. More importantly, our results indicate that our method can be used for hypothesis generation based on automated discovery of novel, disease-related functional subnetworks, which would otherwise require extensive and laborious manual assessment. Availability and implementation: metaModules is available at https://bitbucket.org/alimay/metamodules/ Supplementary information: Supplementary data are available at Bioinformatics online.
UR - http://www.scopus.com/inward/record.url?scp=84973369805&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btv526
DO - 10.1093/bioinformatics/btv526
M3 - Article
C2 - 26342232
AN - SCOPUS:84973369805
SN - 1367-4803
VL - 32
SP - 1678
EP - 1685
JO - Bioinformatics
JF - Bioinformatics
IS - 11
ER -