MODEL-FREE LINKAGE ANALYSIS USING LIKELIHOODS

Misspecification of transmission model parameters can produce artifact ually negative lod scores at small recombination fractions and in mult ipoint analysis. To avoid this problem, we have tried to devise a test that aims to detect a genetic effect at a particular locus, rather th an attempting to estimate the map position of a locus with specified e ffect. Maximizing likelihoods over transmission model parameters, as w ell as linkage parameters, can produce seriously biased parameter esti mates and so yield tests that lack power for the detection of linkage. However, constraining the transmission model parameters to produce th e correct population prevalence largely avoids this problem. For compu tational convenience, we recommend that the likelihoods under linkage and non-linkage are independently maximized over a limited set of tran smission models, ranging from Mendelian dominant to null effect and fr om null effect to Mendelian recessive. In order to test for a genetic effect at a given map position, the likelihood under linkage is maximi zed over admixture, the proportion of families linked. Application to simulated data for a wide range of transmission models in both affecte d sib pairs and pedigrees demonstrates that the new method is well beh aved under the null hypothesis and provides a powerful test for linkag e when it is present. This test requires no specification of transmiss ion model parameters, apart from an approximate estimate of the popula tion prevalence. It can be applied equally to sib pairs and pedigrees, and, since it does not diminish the lod score at test positions very close to a marker, it is suitable for application to multipoint data.