Strain-level transmission inference across multi-kingdom metagenomic data using TRACS

Abstract

Coexisting strains of the same species within metagenomic data pose a substantial challenge to inferring transmission of pathogenic and commensal microbes. Here we present TRAnsmision Clustering of Strains (TRACS), a highly accurate algorithm for estimating genetic distances between strains at the level of individual single nucleotide polymorphisms, which is robust to intra-species diversity within the host. Analysis of faecal microbiota transplantation datasets and extensive simulations demonstrates that TRACS outperforms existing methods. We use TRACS to infer transmission networks in patients colonized with multiple strains, including severe acute respiratory syndrome coronavirus 2 amplic..