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Haplotype association analyses in resources of mixed structure using Monte Carlo testing
Authors:Ryan?Abo  author-information"  >  author-information__contact u-icon-before"  >  mailto:ryan.abo@hsc.utah.edu"   title="  ryan.abo@hsc.utah.edu"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Jathine?Wong,Alun?Thomas,Nicola?J?Camp
Affiliation:1.Department of Biomedical Informatics,University of Utah,Salt Lake City,USA;2.Department of Internal Medicine,University of Utah,Salt Lake City,USA
Abstract:

Background  

Genomewide association studies have resulted in a great many genomic regions that are likely to harbor disease genes. Thorough interrogation of these specific regions is the logical next step, including regional haplotype studies to identify risk haplotypes upon which the underlying critical variants lie. Pedigrees ascertained for disease can be powerful for genetic analysis due to the cases being enriched for genetic disease. Here we present a Monte Carlo based method to perform haplotype association analysis. Our method, hapMC, allows for the analysis of full-length and sub-haplotypes, including imputation of missing data, in resources of nuclear families, general pedigrees, case-control data or mixtures thereof. Both traditional association statistics and transmission/disequilibrium statistics can be performed. The method includes a phasing algorithm that can be used in large pedigrees and optional use of pseudocontrols.
Keywords:
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