Contamination source modeling with SCRuB improves cancer phenotype prediction from microbiome data.

ABSTRACT: Sequencing-based approaches for the analysis of microbial communities are susceptible to contamination, which could mask biological signals or generate artifactual ones. Methods for in silico decontamination using controls are routinely used, but do not make optimal use of information shared across samples and cannot handle taxa that only partially originate in contamination or leakage of biological material into controls. Here we present Source tracking for Contamination Removal in microBiomes (SCRuB), a probabilistic in silico decontamination method that incorporates shared information across multiple samples and controls to precisely identify and remove contamination. We validate the accuracy of SCRuB in multiple data-driven simulations and experiments, including induced contamination,

SUBMITTER: Austin GI 

PROVIDER: S-EPMC10504420 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature