Online Program

338566
Imputing gene expression in uncollected tissues within and beyond GTEx


Tuesday, November 3, 2015 : 11:20 a.m. - 11:45 a.m.

Lin Chen, PhD, Public Health Sciences, University of Chicago, Chicago, IL
Gene expression and its regulation can vary substantially across tissue types.  In order to generate new knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. Many tissue types are hard to access and are not collected on every GTEx individual. The accessibility of certain tissue types also greatly limits the feasibility and scale of multitissue expression studies in non-GTEx populations.  We develop a multitissue imputation approach to impute gene expression in uncollected or inaccessible tissues. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrate that transcriptome data from uncollected GTEx tissues can be imputed by harnessing eQTL and tissue-tissue correlation. More importantly, we show that using GTEx data as a reference, one can impute expression in inaccessible tissues in other expression studies.

Learning Areas:

Biostatistics, economics
Public health biology

Learning Objectives:
Describe issues with GTEx analysis. Evaluate gene expression analysis with uncollected tissues.

Keyword(s): Biostatistics, Genetics

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am an Assistant Professor of Biostatistics and an expert in gene expression analysis.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 4112.0: Statistical Genomics