Buetow K H
Division of Population Science, Fox Chase Cancer Center, Philadelphia, PA 19111.
Am J Hum Genet. 1991 Nov;49(5):985-94.
Because of the availability of efficient, user-friendly computer analysis programs, the construction of multilocus human genetic maps has become commonplace. At the level of resolution at which most of these maps have been developed, the methods have proved to be robust. This may not be true in the construction of high-resolution linkage maps (3-cM interlocus resolution or less). High-resolution meiotic maps, by definition, have a low probability of recombination occurring in an interval. As such, even low frequencies of errors in typing (1.5% or less) may influence mapping outcomes. To investigate the influence of aberrant observations on high-resolution maps, a Monte Carlo simulation analysis of multipoint linkage data was performed. Introduction of error was observed to reduce power to discriminate orders, dramatically inflate map length, and provide significant support for incorrect over correct orders. These results appear to be due to the misclassification of nonrecombinant gametes as multiple recombinants. Chi 2-Like goodness-of-fit analysis appears to be quite sensitive to the appearance of misclassified gametes, providing a simple test for aberrant data sets. Multiple pairwise likelihood analysis appears to be less sensitive than does multipoint analysis and may serve as a check for map validity.
由于高效、用户友好的计算机分析程序的出现，多位点人类遗传图谱的构建已变得很常见。在大多数此类图谱所构建的分辨率水平上，这些方法已被证明是可靠的。但在构建高分辨率连锁图谱（基因座间分辨率为3厘摩或更低）时可能并非如此。根据定义，高分辨率减数分裂图谱在一个区间内发生重组的概率较低。因此，即使分型错误的频率很低（1.5%或更低）也可能影响图谱构建结果。为了研究异常观测值对高分辨率图谱的影响，对多点连锁数据进行了蒙特卡罗模拟分析。观察到引入误差会降低辨别顺序的能力，大幅增加图谱长度，并为错误顺序而非正确顺序提供显著支持。这些结果似乎是由于非重组配子被错误分类为多个重组体所致。类似卡方的拟合优度分析似乎对错误分类配子的出现非常敏感，为异常数据集提供了一个简单的检验方法。多重成对似然分析似乎比多点分析的敏感性要低，可作为图谱有效性的一种检验。
