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Title: Some statistical issues in pathway analysis of genome-wide studies
Abstract:
Pathway analysis (or gene set analysis) have become increasingly popular for analyzing genomewide studies. These approaches aim to increase power by combining association signals from
multiple genes in the same pathway. In this talk, I will introduce basic concepts and procedures
for pathway analysis, discuss the particular methodological challenges at each stage of the
analysis and review recently developed tools in this area.
Topics:
1. Introduce pathway analysis for genome-wide studies (e.g. gene expression experiments,
genome-wide association studies)
2. Review procedures of pathway analysis and survey recently developed tools
3. Discuss particular methodological challenges at each stage of the analysis
Goals:
1. To understand the basic concepts in pathway analysis
2. To illustrate the use of pathway analysis for gene expression experiments
Intended Audience:
Researchers who are interested in conducting pathway analysis for their studies.
Speaker Description:
Lily Wang is an Assistant Professor in Biostatistics at Vanderbilt University School of Medicine.
Her main research interest is to develop effective statistical models for the analysis of high
throughput genomics datasets. Over the past several years, she has developed several innovative
mixed effects models for pathway-based analysis of gene expression experiments and genomewide association studies, which were published in PLoS Genetics, Statistical Applications in
Genetics and Molecular Biology, Bioinformatics and Genomics recently. She is a member of the
Statistics and Methodology Core at the Kennedy Center and provides support in design and
analyses related to clinical trials, microarray studies, and other biological experiments.