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• W2034018992 abstract "In genome-wide screens of genetic marker loci, non-mendelian inheritance of a marker is taken to indicate its vicinity to a disease locus. Heritable complex traits are thought to be under the influence of multiple possibly interacting susceptibility loci yet the most frequently used methods of linkage and association analysis focus on one susceptibility locus at a time. Here we introduce log-linear models for the joint analysis of multiple marker loci and interaction effects between them. Our approach focuses on affected sib pair data and identical by descent (IBD) allele sharing values observed on them. For each heterozygous parent, the IBD values at linked markers represent a sequence of dependent binary variables. We develop log-linear models for the joint distribution of these IBD values. An independence log-linear model is proposed to model the marginal means and the neighboring interaction model is advocated to account for associations between adjacent markers. Under the assumption of conditional independence, likelihood methods are applied to simulated data containing one or two susceptibility loci. It is shown that the neighboring interaction log-linear model is more efficient than the independence model, and incorporating interaction in the two-locus analysis provides increased power and accuracy for mapping of the trait loci." @default.
• W2034018992 created "2016-06-24" @default.
• W2034018992 creator A5018043030 @default.
• W2034018992 creator A5042072885 @default.
• W2034018992 date "2002-11-21" @default.
• W2034018992 modified "2023-09-29" @default.
• W2034018992 title "Log-Linear Models for Gene Mapping with Affected Sib Pair Data" @default.
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• W2034018992 doi "https://doi.org/10.1159/000066196" @default.
• W2034018992 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/12435886" @default.
• W2034018992 hasPublicationYear "2002" @default.
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