Testing linkage disequilibrium in sibships.
We describe the use of multivariate regression for testing allelic association in the presence of linkage, using marker genotype data from sibships. The test is valid, provided that the correct mean structure is modeled but does not require the correlation structure within families to be specified. The test can be implemented using standard statistical software such as the SAS programming language. In a simulation study, we evaluated this new test in comparison with one from a standard, matched-case-control analysis. First, we noted that the genetic effect needed to be quite extreme before residual familial correlation due to linkage led to false inference using the standard, matched-pair analysis. Second, we showed that under examples of extreme residual familial correlation, the new test had the correct test size. Third, we found that the test was more powerful than the sibship disequilibrium test of Horvath and Laird. Finally, we concluded that although the standard analysis may lead to correct inference for practical purposes, the new test is valid, even under extreme residual familial correlation and with no cost in power at the causal locus.
Siegmund
K D
KD
Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA. kims@usc.edu
Langholz
B
B
Kraft
P
P
Thomas
D C
DC
D000483:Alleles; D016022:Case-Control Studies; D002874:Chromosome Mapping / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D005787:Gene Frequency / Q000235:genetics; D030342:Genetic Diseases, Inborn / Q000453:epidemiology / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium / Q000235:genetics*; D016555:Matched-Pair Analysis; D008957:Models, Genetic; D015999:Multivariate Analysis; D009679:Nuclear Family; D015203:Reproducibility of Results; D018401:Sample Size; D012984:Software