Allison D B, Fernández J R, Heo M, Beasley T M
Obesity Research Center, St. Luke's/Roosevelt Hospital, Columbia University College of Physicians & Surgeons, New York, NY 10025, USA.
Am J Hum Genet. 2000 Jul;67(1):249-52. doi: 10.1086/302966. Epub 2000 May 11.
Variance components (VC) techniques have emerged as among the more powerful methods for detection of quantitative-trait loci (QTL) in linkage analysis. Allison et al. found that, with particularly marked leptokurtosis in the phenotypic distribution and moderate-to-high residual sibling correlation, maximum likelihood (ML) VC methods may produce a severe excess of type I errors. The new Haseman-Elston (NHE) method is a least-squares-based VC method for mapping of QTL in sib pairs (Elston et al.). Using simulation, we investigate the robustness of the NHE to marked nonnormality, by means of the same distributions and worst-case conditions identified by Allison et al. for the ML approach (i.e., 100 pairs; high residual sibling correlation). Results showed that, when marked nonnormality is present, the NHE can be used without severe type I error-rate inflation, even at very small alpha levels.
方差分量(VC)技术已成为连锁分析中检测数量性状基因座(QTL)的更强大方法之一。艾利森等人发现,在表型分布中具有特别明显的峰度,且同胞间残差相关性为中度至高度时,最大似然(ML)VC方法可能会产生严重的I型错误过量。新的哈斯曼 - 埃尔斯顿(NHE)方法是一种基于最小二乘法的VC方法,用于同胞对中QTL的定位(埃尔斯顿等人)。我们通过模拟,借助艾利森等人针对ML方法确定的相同分布和最坏情况条件(即100对;同胞间残差相关性高),研究NHE对明显非正态性的稳健性。结果表明,当存在明显非正态性时,即使在非常小的α水平下,NHE也可使用而不会出现严重的I型错误率膨胀。