在某些自然不等式限制下两位点重组率的最大似然估计。
Maximum likelihood estimates of two-locus recombination fractions under some natural inequality restrictions.
作者信息
Zhou Ying, Shi Ning-Zhong, Fung Wing-Kam, Guo Jianhua
机构信息
Key Laboratory for Applied Statistics of MOE and School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, PR, China.
出版信息
BMC Genet. 2008 Jan 4;9:1. doi: 10.1186/1471-2156-9-1.
BACKGROUND
The goal of linkage analysis is to determine the chromosomal location of the gene(s) for a trait of interest such as a common disease. Three-locus linkage analysis is an important case of multi-locus problems. Solutions can be found analytically for the case of triple backcross mating. However, in the present study of linkage analysis and gene mapping some natural inequality restrictions on parameters have not been considered sufficiently, when the maximum likelihood estimates (MLEs) of the two-locus recombination fractions are calculated.
RESULTS
In this paper, we present a study of estimating the two-locus recombination fractions for the phase-unknown triple backcross with two offspring in each family in the framework of some natural and necessary parameter restrictions. A restricted expectation-maximization (EM) algorithm, called REM is developed. We also consider some extensions in which the proposed REM can be taken as a unified method.
CONCLUSION
Our simulation work suggests that the REM performs well in the estimation of recombination fractions and outperforms current method. We apply the proposed method to a published data set of mouse backcross families.
背景
连锁分析的目标是确定与感兴趣的性状（如常见疾病）相关的基因在染色体上的位置。三位点连锁分析是多位点问题的一个重要案例。对于三重回交交配的情况，可以通过解析方法找到解决方案。然而，在目前的连锁分析和基因定位研究中，在计算两位点重组率的最大似然估计（MLE）时，对参数的一些自然不等式限制没有得到充分考虑。
结果
在本文中，我们在一些自然且必要的参数限制框架下，对每个家庭有两个后代的未知相位三重回交的两位点重组率估计进行了研究。开发了一种受限期望最大化（EM）算法，称为REM。我们还考虑了一些扩展，其中所提出的REM可作为一种统一方法。
结论
我们的模拟工作表明，REM在重组率估计方面表现良好，并且优于当前方法。我们将所提出的方法应用于已发表的小鼠回交家系数据集。
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