NONPARAMETRIC SIMULATION-BASED STATISTICS FOR DETECTING LINKAGE IN GENERAL PEDIGREES

We present here four nonparametric statistics for linkage analysis tha t test whether pairs of affected relatives share marker alleles more o ften than expected. These statistics are based on simulating the null distribution of a given statistic conditional on the unaffecteds' mark er genotypes. Each statistic uses a different measure of marker sharin g: the SimAPM statistic uses the simulation-based affected-pedigree-me mber measure based on identity-by-state (IBS) sharing. The SimKIN (kin ship) measure is 1.0 for identity-by-descent (IBD) sharing, 0.0 for no IBD sharing, and the kinship coefficient when the IBD status is ambig uous. The simulation-based IBD (SimIBD) statistic uses a recursive alg orithm to determine the probability of two affecteds sharing a specifi c allele IBD. The SimISO statistic is identical to SimIBD, except that it also measures marker similarity between unaffected pairs. We evalu ated our statistics on data simulated under different two-locus diseas e models, comparing our results to those obtained with several other n onparametric statistics. Use of IBD information produces dramatic incr eases in power over the SimAPM method, which uses only IBS information . The power of our best statistic in most cases meets or exceeds the p ower of the other nonparametric statistics. Furthermore, our statistic s perform comparisons between all affected relative pairs within gener al pedigrees and are not restricted to sib pairs or nuclear families.