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Activity Number:
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285
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #310231 |
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Title:
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Genetic Association Analysis Using the Penalized Likelihood Approach
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Author(s):
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Xiwu Lin*+ and Kijoung Song and Daniel Parks and Jie Cheng and Kwan Lee
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Companies:
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GlaxoSmithKline and GlaxoSmithKline and GlaxoSmithKline and GlaxoSmithKline and GlaxoSmithKline
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Address:
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1250 S Collegeville Rd, Collegeville, PA, 19426,
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Keywords:
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penalized likelihood ; genetic association ; penalty function ; SNP
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Abstract:
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With the advances of genotyping technologies, genome-wide association studies with hundreds of thousands of single nucleotide polymorphisms (SNPs) are available. To analyze such kind of genetic data, one usually analyzes each SNP one at a time to examine the association between each SNP and disease status. One big challenge for single SNP approach is the issue of multiple testing. Another issue for such approach is that multiple SNPs might have separately small effects but jointly they might have a large effect on the disease of interest. To overcome the above issues, we use a penalized likelihood approach to analyze the effects of all SNPs on a chromosome level. We propose a weighted penalty function to incorporate the relationship among SNPs. The performance of the proposed method is evaluated using simulation data. An example based on a genetic epidemiology data will be provided.
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