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Abstract Details
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Activity Number:
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183
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #306847 |
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Title:
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Predicting HLA Allele from Genotype Data
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Author(s):
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Yongtao Guan*+
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Companies:
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Address:
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2001 Holcombe Blvd, Houston, TX, 77030, United States
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Keywords:
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HLA subtype ;
MHC ;
linkage disequilibrium ;
genetics
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Abstract:
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Predicting human leukocyte antigen (HLA) subtype is an important problem in statistical genetics that remains an open challenge. The difficulty lies in the complicated linkage disequilibrium pattern in the major histocompatibility complex (MHC) region of the genome that contains HLA alleles. We present a novel statistical method for predicting HLA subtype and demonstrate its effectiveness via cross validation using real data from Wellcome trust case control consortium. The predicting method relies on a two layer clustering model that approximates the coalescence and recombination to quantify patterns of linkage disequilibrium. Since many HLA substypes are rare, the clustering model requires large number of clusters, which makes the computation prohibitively difficult because the model fitting is quadratic in number of clusters for diploid individuals. We developed a novel model fitting scheme that is effectively linear in number of clusters for diploid individuals, which is crucial for successfully predict HLA subtype.
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