Least squares estimation of variance components for linkage

We develop least squares (LS) procedures for variance components estimation in genetic linkage studies. The LS procedure is expressed by simple expres sions, and does not require inversion of large matrices. Simulations compar ing LS with maximum likelihood (ML) procedures for normal data show that bo th yield unbiased estimators, but the efficiency of the LS procedure was le ss than 50% of the ML procedure. For bivariate normal data, the efficiency of the LS procedure relative to the ML method was better, generally over 60 %. For skewed data, the LS method was markedly more efficient than ML for p arameter estimation. The LS method was computationally rapid, over 4,000 ti mes faster than ML estimation for bivariate data. Because ML estimation is time consuming, LS methods are suggested for initial interval mapping with multivariate data. Genet. Epidemiol. 19(Suppl 1):S1-S7, 2000. (C) 2000 Wile y-Liss, Inc.