PT  - JOURNAL ARTICLE
AU  - Yan Ni
AU  - Gang Yu
AU  - Yongqiong Deng
AU  - Xiaojiao Zheng
AU  - Tianlu Chen
AU  - Junfen Fu
AU  - Wei Jia
TI  - MMCA: a Web-based Server for the Microbiome and Metabolome Correlation Analysis
AID  - 10.1101/678813
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 678813
4099  - http://biorxiv.org/content/early/2019/06/21/678813.short
4100  - http://biorxiv.org/content/early/2019/06/21/678813.full
AB  - Background In 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 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 correlation analysis pipeline (MMCA) to meet the urgent needs for tools that effectively integrate microbiome and metabolome data to derive biological insights.Results To make the MMCA pipeline available to a wider research community, we have implemented a web server (http://mmca.met-bioinformatics.cn). MMCA integrates a variety of statistical analysis methods in order to obtain reliable results from multiple analyses, including univariate analysis and multivariate modeling. MMCA also provides KEGG-based functional network analysis in order to investigate their biological interplay between metabolites and microbes. To make it more convenient, an html-based report is available for overview and can be downloaded for later use.Conclusions MMCA allows users to upload annotated microbiome and metabolome data, provides a user-friendly interface to analyze and visualize the complex interplay between microbiome and metabolome, and helps users to develop mechanistic hypothesis for nutritional and personalized therapies of diseases.