Two-locus disease models with two marker loci: the power of
affected-sib-pair tests
M. Knapp, S.A. Seuchter, M.P. Baur
American Journal of Human Genetics, 55(5),1030-1041
(Nov 1994).
Abstract
Recently, Schork et al. found that two-trait-locus, two-marker-locus
(parametric) linkage analysis can provide substantially more linkage
information than can standard one-trait-locus, one-marker-locus
methods. However, because of the increased burden of computation,
Schork et al. do not expect that their approach will be applied in
an initial genome scan. Further, the specification of a suitable
two-locus segregation model can be crucial. Affected-sibpair tests
are computationally simple and do not require an explicit
specification of the disease model. In the past, however, these
tests mainly have been applied to data with a single marker locus.
Here, we consider sib-pair tests that make it possible to analyze
simultaneously two marker loci. The power of these tests is
investigated for different (epistatic and heterogeneous)
two-trait-locus models, each trait locus being linked to one of the
marker loci. We compare these tests both with the test that is
optimal for a certain model and with the strategy that analyzes each
marker locus separately. The results indicate that a straightforward
extension of the well-known mean test for two marker loci can be
much more powerful than single-marker-locus analysis and that is
power is only slightly inferior to the power of the optimal test.
Allele-sharing linkage analysis