Method and system for identification of key driver organisms from microbiome / metagenomics studies

Abstract

The present disclosure addresses the technical problem related to the identification of microbial basis of a disease in microbiome. A system and method for identification of key driver responsible for bringing a change in a microbial population has been disclosed. A subset of common taxa between the 'control' and ‘case’ dataset is chosen and corresponding microbial association network is created. The method involves the characterization of the important community level changes between two association networks (‘control’ and ‘case’) that are obtained for a particular disease or condition. A taxon in the diseased state with an altered set of associations (identified by a high network shift score), while still being increasingly important (identified with a positive increase in betweenness) for the whole network, necessarily holds a key significance in the identification of key driver.