Szatkiewicz Jin P, T Cuenco Karen, Feingold Eleanor
Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Am J Hum Genet. 2003 Oct;73(4):874-85. doi: 10.1086/378590. Epub 2003 Sep 10.
Extreme discordant sibling pairs (EDSPs) are theoretically powerful for the mapping of quantitative-trait loci (QTLs) in humans. EDSPs have not been used much in practice, however, because of the need to screen very large populations to find enough pairs that are extreme and discordant. Given appropriate statistical methods, another alternative is to use moderately discordant sibling pairs (MDSPs)--pairs that are discordant but not at the far extremes of the distribution. Such pairs can be powerful yet far easier to collect than extreme discordant pairs. Recent work on statistical methods for QTL mapping in humans has included a number of methods that, though not developed specifically for discordant pairs, may well be powerful for MDSPs and possibly even EDSPs. In the present article, we survey the new statistics and discuss their applicability to discordant pairs. We then use simulation to study the type I error and the power of various statistics for EDSPs and for MDSPs. We conclude that the best statistic(s) for discordant pairs (moderate or extreme) is (are) to be found among the new statistics. We suggest that the new statistics are appropriate for many other designs as well-and that, in fact, they open the way for the exploration of entirely novel designs.
极端不一致同胞对（EDSPs）在理论上对于人类数量性状基因座（QTLs）的定位具有强大作用。然而，由于需要筛查非常大的群体以找到足够多的极端且不一致的对，EDSPs在实践中并未得到广泛应用。如果有合适的统计方法，另一种选择是使用中度不一致同胞对（MDSPs）——即不一致但并非处于分布最极端位置的对。这类对可能很有效，而且比极端不一致对更容易收集。近期关于人类QTL定位统计方法的研究包括一些虽不是专门针对不一致对开发，但可能对MDSPs甚至EDSPs也很有效的方法。在本文中，我们综述了这些新统计方法，并讨论它们对不一致对的适用性。然后我们通过模拟研究了各种统计方法对EDSPs和MDSPs的I型错误和检验效能。我们得出结论，对于不一致对（中度或极端）而言，最佳统计方法可在这些新统计方法中找到。我们认为这些新统计方法也适用于许多其他设计——实际上，它们为探索全新的设计开辟了道路。
