Bayesian clustering algorithms ascertaining spatial population structure:: a new computer program and a comparison study
Bayesian clustering algorithms ascertaining spatial population structure:: a new computer program and a comparison study
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DOI：
10.1111/j.1471-8286.2007.01769.x
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发表时间：
2007-09-01
期刊：
影响因子：
--
通讯作者：
Francois, Olivier
中科院分区：
文献类型：
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作者：
Chen, Chibiao;Durand, Eric;Francois, Olivier
在模拟数据的基础上，本研究比较了贝叶斯聚类计算机程序STRUCTURE，GENELAND，GENECLUST和一个新的程序TESS的相对性能。虽然这四个程序可以从多位点基因型检测群体遗传结构，但只有最后三个程序包括地理数据的同时分析。这些程序进行比较，他们的能力，以推断人口的数量，估计成员的概率，并检测遗传的不连续性和倾斜的变化。结果表明，结合使用TESS和结构分析提供了一种方便的方法来解决空间人口结构的推断。
On the basis of simulated data, this study compares the relative performances of the Bayesian clustering computer programs STRUCTURE, GENELAND, GENECLUST and a new program named TESS. While these four programs can detect population genetic structure from multilocus genotypes, only the last three ones include simultaneous analysis from geographical data. The programs are compared with respect to their abilities to infer the number of populations, to estimate membership probabilities, and to detect genetic discontinuities and clinal variation. The results suggest that combining analyses using TESS and STRUCTURE offers a convenient way to address inference of spatial population structure.