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Abstract #166835

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Sierra Li, Division of Oncology Biostatistics, Johns Hopkins University, Johns Hopkins School of Medicine, 550 N. Broadway Suite 1103, Baltimore, MD 21205, 410- 955-0859, sierrali@jhmi.edu and Giovanni Parmigiani, Department of Biostatistics, Johns Hopkins University, Bloomberg School of Public Health, 615 N. Wolfe St., Baltimore, MD 21205.

High-throughput gene profiling measures the expression of thousand of genes simultaneously. Gene set enrichment analysis examines the pre-defined, biologically meaningful sets of genes with increased power and robustness to find subtle changes. With gene expression data measured by multiple profiles, such as in different cell lines and under different drug treatments, it is of great interest to elucidate which and how the enrichment differs among experiment profiles. We conceptualize the common and differential enrichment with cross-profile mean and variance for the coefficients in the regression model. A Bayesian hierarchical model is developed to select variables corresponding to common and differential enrichment. To evaluate the performance of our model, we applied it to simulated data with various level of common and different enrichment, and compare the variable selection accuracy to the model with no distinction of enrichment type. Finally, we demonstrate that our model is generally applicable to parametric gene set enrichment analysis by analyzing KEGG pathways in two cancer studies.

Learning Objectives:

• - Mythological development of multivariate Bayesian variable selection motivated by the concept of common and differential enrichment in gene-set analysis
• - Advantage of a hierarchical model for cross-experiment mean and variance
• - Evaluate and compare the performance of the Bayesian hierarchical model with multiple simulated data
• - Application in gene set enrichment analysis with experimental data

Keywords: Genetics, Biostatistics

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

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.

• Audio (mp3) recording
• Slides (pdf) or Handout