Biostatistics Weekly Seminar

Joint analysis of gene expression and genome-wide association studies reveals genes responsible for common disease risk

Nicholas Mancuso, PhD
      Postdoctoral fellow
      Department of Pathology and Laboratory Medicine
      Geffen School of Medicine
      University of California, Los Angeles

Genome-wide association studies (GWASs) have been successful at mapping common disease risk to specific genomic regions. However, with a few notable exceptions, the underlying causal mechanisms responsible for inherited disease risk are still unknown. In this talk I will present computational approaches that integrate total and splicing gene expression with large-scale GWASs to identify genes responsible for disease risk. In particular, I will introduce methods to test for association between gene or isoform-specific expression and complex trait using publicly available summary statistics. I illustrate its use with results integrating gene expression from 48 gene expression panels with summary data from 30 publicly-available GWASs and a recent large-scale GWAS in prostate cancer. Lastly, I will present recent work to statistically fine-map gene-disease associations in a Bayesian context to produce credible-sets of genes with motivation through lipids GWAS.

MRBIII, Room 1220
14 November 2018

Speaker Itinerary

Topic revision: r1 - 05 Nov 2018, ThomasStewart

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