Xu Xin, Tian Lu, Wei L J
Program for Population Genetics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA.
Biostatistics. 2003 Apr;4(2):223-9. doi: 10.1093/biostatistics/4.2.223.
A robust statistical method to detect linkage or association between a genetic marker and a set of distinct phenotypic traits is to combine univariate trait-specific test statistics for a more powerful overall test. This procedure does not need complex modeling assumptions, can easily handle the problem with partially missing trait values, and is applicable to the case with a mixture of qualitative and quantitative traits. In this note, we propose a simple test procedure along this line, and show its advantages over the standard combination tests for linkage or association in the literature through a data set from Genetic Analysis Workshop 12 (GAW12) and an extensive simulation study.
一种用于检测基因标记与一组不同表型性状之间连锁或关联的强大统计方法，是将单变量性状特异性检验统计量组合起来，以进行更强大的总体检验。该方法不需要复杂的建模假设，能够轻松处理部分性状值缺失的问题，并且适用于定性和定量性状混合的情况。在本笔记中，我们提出了一种沿此思路的简单检验方法，并通过遗传分析研讨会12（GAW12）的一个数据集以及广泛的模拟研究，展示了其相对于文献中用于连锁或关联的标准组合检验的优势。
