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Activity Number:
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78
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Type:
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Invited
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Date/Time:
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Monday, August 4, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #300048 |
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Title:
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Methods for Incorporating Biological Knowledge into Analysis of Genome-Wide Association Studies
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Author(s):
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Hongzhe Li*+
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Companies:
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University of Pennsylvania
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Address:
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Department of Biostatistics and Epidemiology , Philadelphia, PA, 19104,
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Keywords:
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group additive regression ; pathways and networks ; hidden Markov random fields ; protein-protein interaction
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Abstract:
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Genome-wide association (GWA) studies have become increasingly popular as a powerful tool for the identification of the disease-causing germline genetic variants. The commonly used analytic method has been mainly single SNP or SNP-SNP pair analyses, coupled with statistical strategies for controlling multiple comparisons. However, this simple approach can lead to both false positive and false negative identification of the relevant SNPs due to both high-dimensionality of the data and the complex genetic architecture of complex diseases. One solution to this problem is to integrate other biologically relevant information into the analysis of such GWA studies. I will present several statistical methods for incorporating the SNP/gene annotations and the pathways information into analysis of these data and demonstrate the methods using a case-control GWA study of neuroblastoma.
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