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Activity Number:
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67
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
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Sponsor:
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ENAR
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| Abstract - #309288 |
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Title:
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Combined Linkage and Association Mapping of Quantitative Trait Loci with Missing Genotype Data
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Author(s):
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Ruzong Fan and Lian Liu*+ and Jeesun Jung and Ming Zhong
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Companies:
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Texas A&M University and Texas A&M University and Indiana University and Texas A&M University
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Address:
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Dept of Statistics, College Station, TX, 77843,
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Keywords:
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Missing genotype ; Linkage disequilibrium mapping ; QTL
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Abstract:
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In this paper, the impact of missing genotypes is investigated for high-resolution combined linkage and association mapping of quantitative trait loci (QTL). We assume that the genotype data are missing completely at random (MCAR). Based on two regression models, F-test statistics are proposed to test association between the QTL and markers. The non-centrality parameter approximations of F-test statistics are derived to make power calculation and comparison, which show that the power of the F-tests is reduced due to the missingness. By simulation study, we show that the two models have reasonable type I error rates for a dataset of moderate sample size. As a practical example, the method is applied to analyze the angiotensin-1 converting enzyme (ACE) data.
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