Gregory D. Sepich‐Poore

Reply to: Caution Regarding the Specificities of Pan-Cancer Microbial Structure

The authors reanalyze their pan-cancer microbiome findings using decontaminated data to address concerns about contamination, batch effects, and machine learning approaches.

BIRDMAn: A Bayesian differential abundance framework that enables robust inference of host-microbe associations

BIRDMAn is a Bayesian framework for differential abundance analysis in microbiome studies, showing improved statistical power and detecting antibiotic effects and cancer classifiers.

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

This paper introduces OGUs, a metagenome analysis method that uses sequence alignment hits to reference genomes for community analysis, showing better performance in predicting biological traits than taxonomic or 16S rRNA methods.