Stringham H M, Boehnke M, Lange K
Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Am J Hum Genet. 1999 Aug;65(2):545-53. doi: 10.1086/302496.
Radiation hybrid (RH) mapping is a powerful method for ordering loci on chromosomes and for estimating the distances between them. RH mapping is currently used to construct both framework maps, in which all markers are ordered with high confidence (e.g., 1,000:1 relative maximum likelihood), and comprehensive maps, which include markers with less-confident placement. To deal with uncertainty in the order and location of markers, marker positions may be estimated conditional on the most likely marker order, plausible intervals for nonframework markers may be indicated on a framework map, or bins of markers may be constructed. We propose a statistical method for estimating marker position that combines information from all plausible marker orders, gives a measure of uncertainty in location for each marker, and provides an alternative to the current practice of binning. Assuming that the prior distribution for the retention probabilities is uniform and that the marker loci are distributed independently and uniformly on an interval of specified length, we calculate the posterior distribution of marker position for each marker. The median or mean of this distribution provides a point estimate of marker location. An interval estimate of marker location may be constructed either by using the 100(alpha/2) and 100(1-alpha)/2 percentiles of the distribution to form a 100(1-alpha) % posterior credible interval or by calculating the shortest 100(1-alpha) % posterior credible interval. These point and interval estimates take into account ordering uncertainty and do not depend on the assumption of a particular marker order. We evaluate the performance of the estimates on the basis of results from simulated data and illustrate the method with two examples.
辐射杂种（RH）图谱构建是一种用于对染色体上的基因座进行排序并估计它们之间距离的强大方法。目前，RH图谱构建既用于构建框架图谱，其中所有标记都以高置信度排序（例如，相对最大似然比为1000:1），也用于构建综合图谱，其中包括放置置信度较低的标记。为了处理标记顺序和位置的不确定性，可以根据最可能的标记顺序估计标记位置，可以在框架图谱上指示非框架标记的合理区间，或者可以构建标记 bins。我们提出了一种统计方法来估计标记位置，该方法结合了所有合理标记顺序的信息，给出了每个标记位置不确定性的度量，并提供了一种替代当前binning做法的方法。假设保留概率的先验分布是均匀的，并且标记基因座在指定长度的区间上独立且均匀分布，我们计算每个标记的标记位置的后验分布。该分布的中位数或均值提供了标记位置的点估计。标记位置的区间估计可以通过使用分布的100(α/2)和100(1 - α)/2百分位数来形成100(1 - α)%后验可信区间，或者通过计算最短的100(1 - α)%后验可信区间来构建。这些点估计和区间估计考虑了排序不确定性，并且不依赖于特定标记顺序的假设。我们根据模拟数据的结果评估估计的性能，并通过两个例子说明该方法。
