Statistics for nonparametric linkage analysis of X-linked traits in general pedigrees

We have compared the power of several allele-sharing statistics for "nonpar ametric" linkage analysis of X-linked traits in nuclear families and extend ed pedigrees. Our rationale was that, although several of these statistics have been implemented in popular software packages, there has been no forma l evaluation of their relative power. Here, we evaluate the relative perfor mance of five test statistics, including two new test statistics. We consid ered sibships of sizes two through four, four different extended pedigrees, 15 different genetic models (12 single-locus models and 3 two-locus models ), and varying recombination fractions between the marker and the trait loc us. We analytically estimated the sample sizes required for 80% power at a significance level of .001 and also used simulation methods to estimate pow er for a sample size of 10 families. We tried to identify statistics whose power was robust over a wide variety of models, with the idea that such sta tistics would be particularly useful for detection of X-linked loci associa ted with complex traits. We found that a commonly used statistic, S-all, ge nerally performed well under various conditions and had close to the optima l sample sizes in most cases but that there were certain cases in which it performed quite poorly. Our two new statistics did not perform any better t han those already in the literature. We also note that, under dominant and additive models, regardless of the statistic used, pedigrees with all-femal e siblings have very little power to detect X-linked loci.