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pubmed-article:18541055pubmed:abstractTextLocalization of complex traits by genetic linkage analysis may involve exploration of a vast multidimensional parameter space. The posterior probability of linkage (PPL), a class of statistics for complex trait genetic mapping in humans, is designed to model the trait model complexity represented by the multidimensional parameter space in a mathematically rigorous fashion. However, the method requires the evaluation of integrals with no functional form, making it difficult to compute, and thus further test, develop and apply. This paper describes MLIP, a multiprocessor two-point genetic linkage analysis system that supports statistical calculations, such as the PPL, based on the full parameter space implicit in the linkage likelihood.lld:pubmed
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pubmed-article:18541055pubmed:authorpubmed-author:VielandVeroni...lld:pubmed
pubmed-article:18541055pubmed:authorpubmed-author:SegreAlberto...lld:pubmed
pubmed-article:18541055pubmed:authorpubmed-author:GovilManikaMlld:pubmed
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pubmed-article:18541055pubmed:volume9 Suppl 6lld:pubmed
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pubmed-article:18541055pubmed:dateRevised2010-11-18lld:pubmed
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pubmed-article:18541055pubmed:articleTitleMLIP: using multiple processors to compute the posterior probability of linkage.lld:pubmed
pubmed-article:18541055pubmed:affiliationDepartment of Oral Biology and Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. govil@pitt.edulld:pubmed
pubmed-article:18541055pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:18541055pubmed:publicationTypeResearch Support, U.S. Gov't, Non-P.H.S.lld:pubmed
pubmed-article:18541055pubmed:publicationTypeResearch Support, N.I.H., Extramurallld:pubmed