GAUSSIAN MODELS FOR GENETIC-LINKAGE ANALYSIS USING COMPLETE HIGH-RESOLUTION MAPS OF IDENTITY BY DESCENT

Gaussian-process models are developed to detect genetic linkage using complete high-resolution maps of identity by descent between affected relative pairs. Approximations are given for the significance level an d power of the likelihood-ratio test of no linkage and for likelihood- ratio confidence regions for trait loci. The sample sizes required to detect linkage by using different classes of affected relative pairs a re compared, and the problem of combining data from different classes of relatives is discussed.