Events
FDS Statistics & Data Science Seminar
Statistical and computational methods for genetic and genomic studies
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Speaker: Xiang Zhou Professor University of Michigan Monday, February 3, 2025 11:30AM - 1:00PM Lunch at 11:30am in room 1307
Talk at 12:00-1:00pm in room 1327A and via Webcast: https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=7b56c54c-e254-4cd4-bd46-b25a013eb54c |
Abstract: I will talk about a few statistical and computational methods we have developed over the past few years to give you a flavor of the type of work we do in our group. My talk will focus on two distinct application areas: genome-wide association studies and spatial multi-omics studies. Specifically, I will talk about MESuSiE, a scalable multi-ancestry variational fine-mapping method that accounts for the diverse linkage disequilibrium pattern observed in different ancestries while explicitly modeling both shared and ancestry-specific causal SNPs with a unique re-parameterization for effective variational inference. I will talk about SPARK, a method that allows for rigorous statistical analysis of spatial expression patterns in spatial transcriptomics, along with its non-parametric extension, SPARK-X, for scalable detection of spatially expressed genes in large spatial transcriptomic studies. If time allows, I will also talk about Dirichlet process regression, or DPR, a non-parametric Bayesian regression method that flexibly and adaptively models the effect size distribution to enable accurate and robust polygenic risk prediction across a broad spectrum of genetic architectures, as well as a spatially informed cell type deconvolution method, CARD, that leverages cell type specific expression information from single cell RNA sequencing for the deconvolution of spatial transcriptomics.
Speaker bio: Dr. Xiang Zhou is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health and serves as an Assistant Director at the University of Michigan Precision Health. He has held the rank of Professor since 2023. Dr. Zhou joined the department as an Assistant Professor in 2014, was named the John G. Searle Assistant Professor in 2018-2019, and served as an Associate Professor from 2019 to 2023. Prior to joining the University of Michigan, he was the William H. Kruskal Instructor in the Department of Statistics at the University of Chicago from 2013 to 2014. Dr. Zhou earned an MS in Statistics in 2009 (advisor: Prof. Scott Schmidler) and a PhD in Neurobiology in 2010 (advisor: Prof. Fan Wang), both from Duke University. He completed a postdoctoral fellowship with Prof. Matthew Stephens in the Department of Statistics at the University of Chicago from 2010 to 2013. Currently, he serves as an Associate Editor for the Journal of the American Statistical Association, Annals of Applied Statistics, and PLOS Genetics. He previously served as the Program Chair of the Section on Statistics in Genomics and Genetics in the American Statistical Association.
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