Song Kyunghee K, Feingold Eleanor, Weeks Daniel E
Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Am J Hum Genet. 2002 Jan;70(1):181-91. doi: 10.1086/338308. Epub 2001 Nov 21.
We have compared the power of several allele-sharing statistics for "nonparametric" linkage analysis of X-linked traits in nuclear families and extended pedigrees. Our rationale was that, although several of these statistics have been implemented in popular software packages, there has been no formal evaluation of their relative power. Here, we evaluate the relative performance of five test statistics, including two new test statistics. We considered sibships of sizes two through four, four different extended pedigrees, 15 different genetic models (12 single-locus models and 3 two-locus models), and varying recombination fractions between the marker and the trait locus. We analytically estimated the sample sizes required for 80% power at a significance level of.001 and also used simulation methods to estimate power for a sample size of 10 families. We tried to identify statistics whose power was robust over a wide variety of models, with the idea that such statistics would be particularly useful for detection of X-linked loci associated with complex traits. We found that a commonly used statistic, S(all), generally performed well under various conditions and had close to the optimal sample sizes in most cases but that there were certain cases in which it performed quite poorly. Our two new statistics did not perform any better than those already in the literature. We also note that, under dominant and additive models, regardless of the statistic used, pedigrees with all-female siblings have very little power to detect X-linked loci.
我们比较了几种等位基因共享统计方法在核心家庭和扩展家系中对X连锁性状进行“非参数”连锁分析的效能。我们的基本原理是，尽管这些统计方法中的几种已在流行的软件包中实现，但尚未对它们的相对效能进行正式评估。在此，我们评估了五种检验统计量的相对性能，包括两种新的检验统计量。我们考虑了大小为2至4的同胞对、四种不同的扩展家系、15种不同的遗传模型（12种单基因座模型和3种双基因座模型），以及标记与性状基因座之间不同的重组率。我们通过分析估计了在显著性水平为0.001时达到80%效能所需的样本量，并且还使用模拟方法估计了10个家庭样本量的效能。我们试图识别出在各种模型中效能稳健的统计量，认为这样的统计量对于检测与复杂性状相关的X连锁基因座特别有用。我们发现，一种常用的统计量S(all)，在各种条件下通常表现良好，并且在大多数情况下接近最优样本量，但在某些情况下其表现相当差。我们的两种新统计量并不比文献中已有的统计量表现更好。我们还注意到，在显性和加性模型下，无论使用何种统计量，全为女性同胞的家系检测X连锁基因座的效能都非常低。
