Thomas Alun
Department of Biomedical Informatics, Genetic Epidemiology, University of Utah, Salt Lake City, Utah 84108, USA.
Hum Hered. 2007;64(1):16-26. doi: 10.1159/000101419. Epub 2007 Apr 27.
We review recent developments of MCMC integration methods for computations on graphical models for two applications in statistical genetics: modelling allelic association and pedigree based linkage analysis. We discuss and illustrate estimation of graphical models from haploid and diploid genotypes, and the importance of MCMC updating schemes beyond what is strictly necessary for irreducibility. We then outline an approach combining these methods to compute linkage statistics when alleles at the marker loci are in linkage disequilibrium. Other extensions suitable for analysis of SNP genotype data in pedigrees are also discussed and programs that implement these methods, and which are available from the author's web site, are described. We conclude with a discussion of how this still experimental approach might be further developed.
我们回顾了马尔可夫链蒙特卡罗（MCMC）积分方法在统计遗传学两个应用中的图形模型计算方面的最新进展：等位基因关联建模和基于家系的连锁分析。我们讨论并举例说明了从单倍体和二倍体基因型估计图形模型，以及MCMC更新方案超出不可约性严格要求的重要性。然后，我们概述了一种在标记位点的等位基因处于连锁不平衡时结合这些方法来计算连锁统计量的方法。还讨论了适用于家系中SNP基因型数据分析的其他扩展，并描述了实现这些方法的程序，这些程序可从作者网站获取。我们最后讨论了这种仍处于实验阶段的方法如何进一步发展。
