PM2RA: A Framework for Detecting and Quantifying Relationship Alterations in Microbial Community
Zhi Liu, Kai Mi, Zhenjiang Zech Xu, Qiankun Zhang, Xingyin Liu
Abstract
The dysbiosis of gut microbiota is associated with the pathogenesis of human diseases. However, observing shifts in the microbe abundance cannot fully reveal underlying perturbations. Examining the relationship alterations (RAs) in the microbiome between health and disease statuses provides additional hints about the pathogenesis of human diseases, but no methods were designed to detect and quantify the RAs between different conditions directly. Here, we present profile monitoring for microbial relationship alteration (PM2RA), an analysis framework to identify and quantify the microbial RAs. The performance of PM2RA was evaluated with synthetic data, and it showed higher specificity and sensitivity than the co-occurrence-based methods. Analyses of real microbial datasets showed that PM2RA was robust for quantifying microbial RAs across different datasets in several diseases. By applying PM2RA, we identified several novel or previously reported microbes implicated in multiple diseases. PM2RA is now implemented as a web-based application available at http://www.pm2ra-xingyinliulab.cn/.