Kevin McGregor

The paper models microbial community diversity using the hierarchical Pitman-Yor process and shows improved diversity estimates when species are missing.

The paper quantifies bias in proportionality-based association metrics for count data and proposes a logit-normal multinomial model to improve accuracy.

The paper introduces a Bayesian factor analysis model with skew-normal priors to improve microbiome data analysis by addressing zero inflation and skewness.

MDiNE estimates differential co-occurrence networks in microbiome studies to analyze how microbial networks change with a binary covariate, outperforming existing methods in simulations and applied to Crohn's disease.

The paper evaluates methods for correcting cell-type heterogeneity in DNA methylation studies and recommends surrogate variable analysis for its consistent performance.