Stephens Matthew, Donnelly Peter
Department of Statistics, University of Washington, Seattle, WA 98195-4322, USA.
Am J Hum Genet. 2003 Nov;73(5):1162-9. doi: 10.1086/379378. Epub 2003 Oct 20.
In this report, we compare and contrast three previously published Bayesian methods for inferring haplotypes from genotype data in a population sample. We review the methods, emphasizing the differences between them in terms of both the models ("priors") they use and the computational strategies they employ. We introduce a new algorithm that combines the modeling strategy of one method with the computational strategies of another. In comparisons using real and simulated data, this new algorithm outperforms all three existing methods. The new algorithm is included in the software package PHASE, version 2.0, available online (http://www.stat.washington.edu/stephens/software.html).
在本报告中,我们比较并对比了三种先前发表的用于从群体样本的基因型数据推断单倍型的贝叶斯方法。我们回顾了这些方法,着重强调它们在所用模型(“先验”)和采用的计算策略方面的差异。我们引入了一种新算法,该算法将一种方法的建模策略与另一种方法的计算策略相结合。在使用真实数据和模拟数据进行的比较中,这种新算法优于所有三种现有方法。新算法包含在PHASE软件包2.0版中,可在线获取(http://www.stat.washington.edu/stephens/software.html)。