TY - JOUR
T1 - M2IA
T2 - a web server for microbiome and metabolome integrative analysis
AU - Ni, Yan
AU - Yu, Gang
AU - Chen, Huan
AU - Deng, Yongqiong
AU - Wells, Philippa M.
AU - Steves, Claire J.
AU - Ju, Feng
AU - Fu, Junfen
PY - 2020/6/1
Y1 - 2020/6/1
N2 - Motivation: Microbiome-metabolome association studies have experienced exponential growth for an in-depth understanding of the impact of microbiota on human health over the last decade. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge due to the lack of a comprehensive computational tool that can facilitate data integration and interpretation. In this study, an automated microbiome and metabolome integrative analysis pipeline (M2IA) has been developed to meet the urgent needs for tools that can effectively integrate microbiome and metabolome data to derive biological insights. Results: M2IA streamlines the integrative data analysis between metabolome and microbiome, from data preprocessing, univariate and multivariate statistical analyses, advanced functional analysis for biological interpretation, to a summary report. The functionality of M2IA was demonstrated using TwinsUK cohort datasets consisting of 1116 fecal metabolites and 16s rRNA microbiome from 786 individuals. Moreover, two important metabolic pathways, i.e. benzoate degradation and phosphotransferase system, were identified to be closely associated with obesity. Contact: [email protected] or [email protected]
AB - Motivation: Microbiome-metabolome association studies have experienced exponential growth for an in-depth understanding of the impact of microbiota on human health over the last decade. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge due to the lack of a comprehensive computational tool that can facilitate data integration and interpretation. In this study, an automated microbiome and metabolome integrative analysis pipeline (M2IA) has been developed to meet the urgent needs for tools that can effectively integrate microbiome and metabolome data to derive biological insights. Results: M2IA streamlines the integrative data analysis between metabolome and microbiome, from data preprocessing, univariate and multivariate statistical analyses, advanced functional analysis for biological interpretation, to a summary report. The functionality of M2IA was demonstrated using TwinsUK cohort datasets consisting of 1116 fecal metabolites and 16s rRNA microbiome from 786 individuals. Moreover, two important metabolic pathways, i.e. benzoate degradation and phosphotransferase system, were identified to be closely associated with obesity. Contact: [email protected] or [email protected]
UR - http://www.scopus.com/inward/record.url?scp=85085905543&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btaa188
DO - 10.1093/bioinformatics/btaa188
M3 - Article
C2 - 32176258
AN - SCOPUS:85085905543
SN - 1367-4811
VL - 36
SP - 3493
EP - 3498
JO - Bioinformatics (Oxford, England)
JF - Bioinformatics (Oxford, England)
IS - 11
ER -