Knapp M, Seuchter S A, Baur M P
Institute for Medical Statistics, University of Bonn, Germany.
Am J Hum Genet. 1994 Nov;55(5):1030-41.
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.
最近，斯科克等人发现，双性状基因座、双标记基因座（参数化）连锁分析比标准的单性状基因座、单标记基因座方法能提供更多的连锁信息。然而，由于计算负担增加，斯科克等人预计他们的方法不会用于初始基因组扫描。此外，合适的双基因座分离模型的设定可能至关重要。受累同胞对检验计算简单，且不需要明确设定疾病模型。然而，过去这些检验主要应用于单标记基因座的数据。在此，我们考虑能够同时分析两个标记基因座的同胞对检验。针对不同的（上位性和异质性）双性状基因座模型研究了这些检验的效能，每个性状基因座与其中一个标记基因座连锁。我们将这些检验与针对特定模型最优的检验以及分别分析每个标记基因座的策略进行比较。结果表明，对两个标记基因座的著名均值检验进行直接扩展，其效能可能远高于单标记基因座分析，且其效能仅略低于最优检验。
