COMPARISON OF NONPARAMETRIC STATISTICS FOR DETECTION OF LINKAGE IN NUCLEAR FAMILIES - SINGLE-MARKER EVALUATION

We have evaluated 23 different statistics, from a total of 10 popular software packages for model-free linkage analysis of nuclear-family da ta, by applying them to single-marker data simulated under several two -locus disease models. The statistics that we examined fall into two b road categories: (1) those that test directly for increased identity-b y-state or identity-by-descent sharing (by use of the programs APM, Ge netic Analysis System [GAS] SIBSTATE and SIBDES, SAGE SIBPAL, ERPA, Si mIBD, and Genehunter NPL) and (2) those that are based on likelihood-r atio tests and that report LOD scores (by use of the programs Splink, SIBPAIR, Mapmaker/Sibs, ASPEX, and GAS SIBMLS). For each of eight two- locus disease models, we analyzed six data sets; the first three data sets consisted of two-child families with both sibs affected and zero, one, or both parents typed, whereas the other three data sets consist ed of four-child families with at least two affected sibs and zero, on e, or both parents typed. We report false-positive rates, overall rank by power, and the power for each statistic. We give rough recommendat ions regarding which programs provide the most powerful tests for link age, as well as the programs to be avoided under certain conditions. F or the likelihood-ratio-based statistics, we examined the effects of v arious treatments of sibships with multiple affected individuals. Fina lly we explored the use of some simple two-of-three composite statisti cs and found that such tests are of only marginal benefit over the mos t powerful single statistic.