Bayes Regularization and Microbiome Multi-Omics: A Two-Tailed Narrative - Dr. Mallick
Biostatistics Branch Seminar Series
April 21, 2020 | 9:00 AM – 10:00 AM
NCI Shady Grove Webex only
Himel Mallick, Ph.D.,
Senior Scientist, Biostatistics,
Merck Research Laboratories
In this talk, I will present a statistical narrative of two seemingly different but equally exciting topics: Bayes regularization and microbiome multi-omics, drawing upon my PhD and postdoc experience of researching in two vastly different academic settings. In the first part of the talk, I will revisit the first principles of variable selection and discuss regularization from a Bayesian vantage point. Several case studies involving both real and synthetic data will be presented for illustration purposes.
In the second part of the talk, I will take a quick detour to discuss the challenges of microbiome multi-omics, which are typically noisy, sparse (zero-inflated), high-dimensional, and extremely non-normal, often arising in the form of count or compositional measurements. I will specifically discuss two recent statistical approaches to data integration in human microbiome studies with an application to the multi-platform genomics data from the recently completed NIH Human Microbiome Project (iHMP).
Finally, I will conclude with comments on the promises and implications of scalable Bayes for large-scale multi-omics data integration and inference for translational epidemiology studies and provide some empirical evidence of using multi-omics both as a multi-purpose biomarker and potential therapeutic target in precision medicine.
Join Via WebEx
Meeting number: 478 574 156
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Access code: 478 574 156