Classifying disease chromosomes arising from multiple founders, with application to fine-scale haplotype mapping.

The availability of high-density haplotype data has motivated several fine-scale linkage disequilibrium mapping methods for locating disease-causing mutations. These methods identify loci around which haplotypes of case chromosomes exhibit greater similarity than do those of control chromosomes. A difficulty arising in such mapping is the possibility that case chromosomes have inherited disease-causing mutations from different ancestral chromosomes (founder heterogeneity). Such heterogeneity dilutes measures of case haplotype similarity. This dilution can be mitigated by separating case chromosomes into subsets according to their putative mutation origin, and searching for an area with excessive haplotype similarity within each subset. We propose a nonparametric method for identifying subsets of case chromosomes likely to share a common ancestral progenitor. By simulation studies and application to published data, we show that the method accurately identifies relatively large subsets of chromosomes that share a common founder. We also show that the method allows more precise estimates of the disease mutation loci than obtained by other fine-scale mapping methods.