BIRDMAn: A Bayesian differential abundance framework that enables robust inference of host-microbe associations
Gibraan Rahman, James T. Morton, Cameron Martino, Gregory D. Sepich‐Poore, Celeste Allaband, Caitlin Guccione, Yang Chen, Daniel Hakim, Mehrbod Estaki, Rob D. Knight
BIRDMAn is a Bayesian framework for differential abundance analysis in microbiome studies, showing improved statistical power and detecting antibiotic effects and cancer classifiers.
bioRxiv · Jan 30, 2023 · PreprintBioinformatics