Two approaches for consolidating results from genome scans of complex traits: Selection methods and scan statistics

This work has two purposes: (i) empirically selecting levels of significanc e that maximize the fraction of markers close to a gene (hit rate) when per forming linkage analyses of simulated data and (ii) evaluating the utility of a previously reported scan statistic on the same data. Genotype data wer e simulated from a trait model of seven susceptibility genes. For purpose ( i), five statistics were evaluated on all marker loci in fifty replicates; two-point lod and heterogeneity lod scores maximized over dominance (mlod, mhlod), a multi-allelic TDT test, an affected sib-pair test (ASP), and a mo del-free test on all sib-pairs (ALL_SIBS). Within each replicate the fracti on of markers (hit rate) significant at specified levels of significance an d also (a) within fifty markers of, or (b) on the same chromosome as a majo r gene was calculated. For purpose (ii), scan statistics of length 15 were calculated for each chromosome and their empirical significance levels esti mated on the basis of 500 replicates generated under no linkage. The scan s tatistic was applied to the mhlod scores from one replicate (Replicate 5). Empirical p-values for the scan statistic were determined by computing mhlo d scores on 500 replicates of simulated null data. For purpose (i), signifi cance levels between 0.001 and 0.01 had the greatest hit rate for all five methods and both criteria. For criterion (a) at the 0.001 level of signific ance, both mlod and mhlod displayed the highest hit rates, approximately 0. 4 for each. For criterion (b), all methods but ALL_SIBS and ASP had hit rat es ranging between 0.4 and 0.5. For purpose (ii), the scan statistic proved equally or more powerful than the single-locus statistic for two of the se ven susceptibility genes while the remaining five genes were not detected. ((C)) 2001 Wiley-Liss, Inc.