A framework for detecting and quantifying relationship alterations in microbial community

Abstract

Dysbiosis of gut microbiota is associated with the pathogenesis of human disease. Observing shifts in the microbe abundance cannot fully reveal underlying perturbations. Examining the relationship alteration (RA) in microbiome between different healthy status provides additional hints about the pathogenesis of human disease. However, no methods were designed to directly detect and quantify the RA between different conditions. Here, we present PM2RA (Profile Monitoring for Microbial Relationship Alteration), an analysis framework to identify and quantify the microbial RAs. The performance of PM2RA were evaluated in synthetic data, and found to show higher specificity and sensitivity than the co-occurrence-based methods. Analyses of real microbial dataset show that PM2RA is robust for quantifying microbial RA across different datasets in several diseases. By applying PM2RA, we identified both previously reported and novel microbes implicated in multiple diseases. The PM2RA is implemented as a web-based application available at http://www.pm2ra-xingyinliulab.cn/.