Novel selection criteria for genome scans of complex traits

Due to their oligogenic inheritance, the identification of susceptibility l oci for complex traits by classical selection criteria has not been very su ccessful. One way to address this problem is to identify statistics that me asure the effect of more than one locus simultaneously. In the approach des cribed here, a p-value is assigned to a combination of loci under the null hypothesis that none of them is linked to the disease locus. In order to ex amine the power of this method to detect multiple loci, the Genetic Analysi s Workshop 12 general population simulated data set was analyzed using vari ance component methods. Using the described novel selection criteria result ed in an increase of power, however, a rejection of the null hypothesis has to be interpreted with care. (C) 2001 Wiley-Liss, Inc.