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M2IA: a web server for microbiome and metabolome integrative analysis

Research output: Contribution to journalArticlepeer-review

Yan Ni, Gang Yu, Huan Chen, Yongqiong Deng, Philippa M. Wells, Claire J. Steves, Feng Ju, Junfen Fu

Original languageEnglish
Pages (from-to)3493-3498
Number of pages6
JournalBioinformatics (Oxford, England)
Volume36
Issue number11
DOIs
Published1 Jun 2020

King's Authors

Abstract

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: yanni617@zju.edu.cn or fjf68@zju.edu.cn

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