Statistical tests for detection of misspecified relationships by use of genome-screen data

Misspecified relationships can have serious consequences for linkage studie s, resulting in either reduced power or false-positive evidence for linkage . If some individuals in the pedigree are untyped, then Mendelian errors ma y not be observed. Previous approaches to detection of misspecified relatio nships by use of genotype data mere developed for sib and half-sib pairs. W e extend the likelihood calculations of Goring and Ott and Boehnke and Cox to more-general relative pairs, for which identity-by-descent (IBD) status is no longer a Markov chain, and me propose a likelihood-ratio test. We als o extend the identity-by-state (IBS)-based test of Ehm and Wagner to nonsib relative pairs. The Likelihood-ratio test has high power, but its drawback s include the need to construct and apply a separate Markov chain for each possible alternative relationship and the need for simulation to assess sig nificance. The IBS-based test is simpler but has lower power. We propose tw o new test Statistics-conditional expected IBD (EIBD) and adjusted IBS (AIB S)-designed to retain the simplicity of IBS while increasing power by takin g into account chance sharing. In simulations, the power of EIBD is general ly close to that of the likelihood-ratio test. The power of AIBS is higher than that of IBS, in all cases considered. We suggest a strategy of initial screening by use of EIBD and AIBS, followed by application of the likeliho od-ratio test to only a subset of relative pairs, identified by use of EIBD and AIBS. We apply the methods to a Genetic Analysis Workshop 11 data set from the Collaborative Study on the Genetics of Alcoholism.