Please join us for our monthly Biomedical Data Science Grand Rounds with Siming Zhao, PhD, Assistant Professor of Biomedical Data Science, Dartmouth Geisel School of Medicine on Thursday, December 9 at 12:00pm via Zoom!

Talk title: "Statistical methods to identify causal genetic variations in human diseases"

Host: Michael Whitfield, PhD

Location: Zoom (no registration required)

Meeting ID: 936 5964 3488

Passcode: 315327

URL:
https://dartmouth.zoom.us/j/93659643488?pwd=WXNKQUwyM2tMVVduaHQyYjZZdDhxUT09

Phone (if needed for audio only): 669-900-6833

Presentation summary
With the advent of next generation sequencing technologies, large scale studies collecting genotypic and phenotypic data for diverse human diseases have been performed. However, how to identify causal genes implicated in human diseases from such data is a challenging task. In this talk, I will present two powerful methods that we recently developed to address this challenge. In the first part, I will present a Bayesian method to identify causal genes implicated in transcriptome-wide association studies (TWAS) of complex traits. TWAS is an increasingly popular method to integrate gene expression information to improve the power to detect genotype-phenotype associations. However, the associations identified from these analyses do not always indicate causal relationships. Our method significantly reduces false positive rate of TWAS. In the second part, I will talk about a method that we developed to identify positively selected genes in cancer. Existing methods for studying selection either lack explicit statistical models or rely on very simple models that do not capture complex features in somatic mutations of driver. Our method is the first statistical framework that models the rich pattern of positive selection in cancer and thus greatly improved power.

Biography
Dr. Siming Zhao obtained her PhD in genetics from Yale University under the supervision of Dr. Richard Lifton. At Yale, she led several cancer-sequencing projects and characterized the genetic landscape of cancers. After that, Dr. Zhao moved to the University of Chicago for her postdoc studies, co-advised by Drs. Matthew Stephens and Xin He. There, she developed computational methods to model selection of somatic mutations and statistical fine mapping methods to identify causal variants for complex traits. Dr. Zhao started her independent research group at Dartmouth in 2021 as Assistant Professor in the Department of Biomedical Data Science at Geisel School of Medicine. The Zhao Lab is interested in exploring the roles of genetic variations in human diseases and developing computational methods to translate large-scale genomics data into disease mechanisms. In the future, the Zhao Lab will focus on developing statistical methods to identify causal genetic variations in human diseases using multidimensional -omics data.