Multipoint Quantitative-Trait Linkage Analysis in General Pedigrees
Laura Almasy,John Blangero +1 more
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TLDR
It is shown how variance-component linkage methods can be used in pedigrees of arbitrary size and complexity, and a general framework for multipoint identity-by-descent (IBD) probability calculations is developed.Abstract:
Multipoint linkage analysis of quantitative-trait loci (QTLs) has previously been restricted to sibships and small pedigrees. In this article, we show how variance-component linkage methods can be used in pedigrees of arbitrary size and complexity, and we develop a general framework for multipoint identity-by-descent (IBD) probability calculations. We extend the sib-pair multipoint mapping approach of Fulker et al. to general relative pairs. This multipoint IBD method uses the proportion of alleles shared identical by descent at genotyped loci to estimate IBD sharing at arbitrary points along a chromosome for each relative pair. We have derived correlations in IBD sharing as a function of chromosomal distance for relative pairs in general pedigrees and provide a simple framework whereby these correlations can be easily obtained for any relative pair related by a single line of descent or by multiple independent lines of descent. Once calculated, the multipoint relative-pair IBDs can be utilized in variance-component linkage analysis, which considers the likelihood of the entire pedigree jointly. Examples are given that use simulated data, demonstrating both the accuracy of QTL localization and the increase in power provided by multipoint analysis with 5-, 10-, and 20-cM marker maps. The general pedigree variance component and IBD estimation methods have been implemented in the SOLAR (Sequential Oligogenic Linkage Analysis Routines) computer package.read more
Citations
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Exact Multipoint Quantitative-Trait Linkage Analysis in Pedigrees by Variance Components
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References
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Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results
Eric S. Lander,Leonid Kruglyak +1 more
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Steven G. Self,Kung Yee Liang +1 more
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Eric S. Lander,Philip Green +1 more
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