Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, Washington, USA.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S48. doi: 10.1186/1471-2156-6-S1-S48.
Many investigators of complexly inherited familial traits bypass classical segregation analysis to perform model-free genome-wide linkage scans. Because model-based or parametric linkage analysis may be the most powerful means to localize genes when a model can be approximated, model-free statistics may result in a loss of power to detect linkage. We performed limited segregation analyses on the electrophysiological measurements that have been collected for the Collaborative Study on the Genetics of Alcoholism. The resulting models are used in whole-genome scans. Four genomic regions provided a model-based LOD > 2 and only 3 of these were detected (p < 0.05) by a model-free approach. We conclude that parametric methods, using even over-simplified models of complex phenotypes, may complement nonparametric methods and decrease false positives.
许多复杂遗传性家族特征的研究者绕过经典的分离分析，直接进行无模型全基因组连锁扫描。因为当可以近似模型时，基于模型或参数的连锁分析可能是定位基因最强大的手段，所以无模型统计可能导致检测连锁的能力丧失。我们对已为酒精遗传合作研究收集的电生理测量结果进行了有限的分离分析。所得到的模型用于全基因组扫描。四个基因组区域提供了基于模型的 LOD>2，只有其中的 3 个（p<0.05）通过无模型方法检测到。我们的结论是，即使使用复杂表型的过于简化的模型，参数方法也可以补充非参数方法并减少假阳性。
