Browning S
Department of Statistics, University of Washington, Seattle, WA 98195-4322, USA.
J Comput Biol. 1998 Summer;5(2):323-34. doi: 10.1089/cmb.1998.5.323.
We consider idealized gamete identity by descent (IBD) data which consists of the lengths of IBD and non-IBD regions along the genome for gametes segregating from two related individuals. Information on the relationship between the individuals is contained in the pattern of lengths, with the power of the likelihood ratio test to reject one relationship in favor of another giving a measure of the information contained in the data. We model crossovers with a Poisson process and, under this assumption, present a novel Monte Carlo method for calculating the likelihood of a particular relationship for a given data set. The method provides a way to calculate the information content of data and find the maximum power that tests of relationship can achieve. Simulated data from cousin and greatgrandparent-greatgrandchild relationships is analyzed as an example.
我们考虑理想化的通过系谱推断的配子同一性（IBD）数据，该数据由沿着基因组的IBD和非IBD区域的长度组成，这些区域来自两个相关个体分离出的配子。个体之间关系的信息包含在长度模式中，似然比检验拒绝一种关系而支持另一种关系的能力给出了数据中所含信息的一种度量。我们用泊松过程对交叉进行建模，并在此假设下，提出一种新颖的蒙特卡罗方法来计算给定数据集特定关系的似然性。该方法提供了一种计算数据信息含量的方法，并找到关系检验所能达到的最大功效。作为示例，分析了来自堂亲关系和曾祖父母 - 曾孙关系的模拟数据。
