Upcoming Colloquia

 Mathematics & Statistics Colloquium

Friday, February 21, 2025, 4:15-5:00pm
 Toomey 254
 Open Q&A forum will occur after the talk.

Dr. Sounak Chakraborty  Dr. Sounak Chakraborty
Associate Professor Department of Statistics University of Missouri

B-MASTER: Scalable Bayesian Multivariate Regression Analysis for Selecting Targeted Essential Regressors to Identify the Key Genera in Microbiome-Metabolite Relation Dynamics

Abstract: The gut microbiome significantly influences responses to cancer therapies, including im-munotherapies, primarily through its impact on the metabolome. Despite some existing studies addressing the effects of specific microbial genera on individual metabolites, there is little to no prior work focused on identifying the key microbiome components at the genus level that shape the overall metabolome profile. To bridge this gap, we introduce B-MASTER (Bayesian Multivariate regression Analysis for Se-lecting Targeted Essential Regressors), a fully Bayesian framework incorporating an l1 penalty to promote sparsity in the coefficient matrix and an l2 penalty to shrink coefficients for non-major covariate compo-nents simultaneously, thereby isolating essential regressors. The method is complemented with a scalable Gibbs sampling algorithm, whose computational speed increases linearly with the number of parameters and remains largely unaffected by sample size and data-specific characteristics for models of fixed dimen-sions. Notably, B-MASTER achieves full posterior inference for models with up to four million parameters within a practical time-frame. Using this approach, we identify key microbial genera influencing the overall metabolite profile, conduct an in-depth analysis of their effects on the most abundant metabolites, and investigate metabolites differentially abundant in colorectal cancer patients. These results provide foun-dational insights into the impact of the microbiome at the genus level on metabolite profiles relevant to cancer, a relationship that remains largely unexplored in the existing literature.
Biographical Sketch: Dr. Sounak Chakraborty is an Associate Professor in the Department of Statis-tics, University of Missouri. He got his Ph.D in Statistics from University of Florida in 2005. Prior to that he got his B.Sc in Statistics from St. Xaviers’ College, Kolkata and his M.Stat from Indian Statistical Insti-tute, Kolkata. His research areas include Bayesian machine learning, variable selection in high dimensional problems, non-linear models for complex data sets, statistical models for multi-platform data integrations,and spatio-temporal analysis. Along with this, he has strong interest in applications of statistical models and tools in areas as bioinformatics, medical science, ecology, business analytics, biomedical engineering,nanotechnology and nanoscience. He has received the prestigious 2019 Albert Winemiller Faculty Research Award at MIZZOU.

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