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Activity Number:
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378
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #304263 |
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Title:
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Bayesian Detection of SNP Interactions Associated with Type-1 Diabetes
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Author(s):
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Jing Zhang*+ and Yu Zhang and Jun S. Liu
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Companies:
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Harvard University and Penn State University and Harvard University
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Address:
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1 Oxford str. , Cambridge, MA, 02138,
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Keywords:
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association study ; haplotype ; Bayesian ; type 1 diabetes ; SNP
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Abstract:
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Under the case-control study setting, we propose a Bayesian method for simultaneously inferring haplotype-blocks and selecting SNPs within blocks that are associated with the disease, either singly or through epistatic interactions with others. Simulation results show that this approach is uniformly more powerful than other epistasis mapping methods including the one of ours. When applied to the WTCCC type-1 diabetes data, the method revealed some interesting two-way interactions within the major histocompatibility complex (MHC) region on chromosome 6. Many interacting SNP pairs are physically distant and separated by several strong recombination hotspots. A very strong interacting region is bounded by a recombination hotspot located in the TAP2 gene.
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