Your browser doesn't support javascript.
loading
M2IA: a web server for microbiome and metabolome integrative analysis.
Ni, Yan; Yu, Gang; Chen, Huan; Deng, Yongqiong; Wells, Philippa M; Steves, Claire J; Ju, Feng; Fu, Junfen.
Afiliação
  • Ni Y; National Clinical Research Center for Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China.
  • Yu G; National Clinical Research Center for Child Health, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310052, China.
  • Chen H; Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province, NMPA Key Laboratory for Testing and Risk Warning of Pharmaceutical Microbiology, Zhejiang Institute of Microbiology, Hangzhou 310012, China.
  • Deng Y; Department of Dermatology and STD, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.
  • Wells PM; Department of Twin Research, Kings College London.
  • Steves CJ; Department of Twin Research, Kings College London.
  • Ju F; Department of Ageing and Health, St Thomas' Hospital, London SE1 7EH, UK.
  • Fu J; School of Engineering, Westlake University.
Bioinformatics ; 36(11): 3493-3498, 2020 06 01.
Article em En | MEDLINE | ID: mdl-32176258
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. AVAILABILITY AND IMPLEMENTATION M2IA is public available at http//m2ia.met-bioinformatics.cn. CONTACT yanni617@zju.edu.cn or fjf68@zju.edu.cn. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metaboloma / Microbiota Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metaboloma / Microbiota Limite: Humans Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China