JSM 2011 Online Program

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Abstract Details

Activity Number: 320
Type: Invited
Date/Time: Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
Sponsor: SSC
Abstract - #303432
Title: Statistical Methods For Integrative Genomics: Challenges And Opportunities
Author(s): Joseph Beyene*+
Companies: McMaster University
Address: , , ,

Due to rapid technological advances in recent years, various types of high-throughput genomic data with varying sizes, structures and complexities have become available. Among them are Single Nucleotide Polymorphisms (SNPs), Copy Number Variations (CNVs) and microarray gene expression measurements. Each of these distinct data types provides a different, partly independent and complementary view of the whole genome. However, understanding functions of genes and other aspects of the genome requires more information than provided by each of the data sets. I will present a conceptual integrative analysis framework and highlight novel statistical methods we have developed recently that can be used to integrate heterogeneous data types in order to answer different scientific questions. In particular, I will describe methods that can be used to answer questions involving class comparisons, quantifying associations between different sets of variables, and predicting clinical outcome. I will provide illustrative examples and discuss methodological issues and challenges.

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