BioinformaticsBioinformaticsPeer-reviewed journal article
M2IA: a Web Server for Microbiome and Metabolome Integrative Analysis
Yan NiiD, Gang YuiD, Huan CheniD, Yongqiong DengiD, Philippa M. WellsiD, Claire Joanne StevesiD, Feng JuiD, Junfen FuiD
Abstract
BackgroundIn the last decade, integrative studies of microbiome and metabolome have experienced exponential growth in understanding their impact on human health and diseases. However, analyzing the resulting multi-omics data and their correlations remains a significant challenge in current studies due to the lack of a comprehensive computational tool to facilitate data integration and interpretation. In this study, we have developed a microbiome and metabolome integrative analysis pipeline (M2IA) to meet the urgent needs for tools that effectively integrate microbiome and metabolome data to derive biological insights.\n\nResultsM2IA streamlines the integrative data analysis between metabolome and microbiome, including both univariate analysis and multivariate modeling methods. KEGG-based functional analysis of microbiome and metabolome are provided to explore their biological interactions within specific metabolic pathways. The functionality of M2IA was demonstrated using TwinsUK cohort data with 1116 fecal metabolites and 16s rRNA microbiome from 786 individuals. As a result, we identified two important pathways, i.e., the benzoate degradation and phosphotransferase system, were closely associated with obesity from both metabolome and microbiome.\n\nConclusionsM2IA is a public available web server (http://m2ia.met-bioinformatics.cn) with the capability to investigate the complex interplay between microbiome and metabolome, and help users to develop mechanistic hypothesis for nutritional and personalized therapies of diseases.
- organism: human
- assay: metagenomics
- assay: metabolomics
- research focus: database / resource
- approach: statistical model
- Citations
- 71
- FWCI
- 3.57
- Field percentile
- top 5%
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