Beta Diversity Diagnosis Project

Photo by rawpixel on Unsplash

We developed a comprehensive framework for evaluating and improving beta diversity measures in microbiome research. Our work highlights the geometric and statistical limitations of widely used dissimilarity measures such as UniFrac, Bray-Curtis, Jaccrad, and introduces diagnostic tools as well as correction methods to enhance their reliability. This framework supports more robust ecological inference. A user-friendly R package is to be available at https://github.com/bioscinema.

Liangliang(Lyon) Zhang
Liangliang(Lyon) Zhang
Assistant Professor

Dr. Zhang’s research interests center around Bayesian inference and prediction, high dimensional models, and complex structured data, such as brain imaging and metagenomic data.