Wageningen University and Research, Biometris, Wageningen, The Netherlands.
Theor Appl Genet. 2011 Jul;123(2):195-205. doi: 10.1007/s00122-011-1576-x. Epub 2011 Apr 7.
Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using real and simulated molecular marker data. Our study also compared the performance of traditional hierarchical clustering with model-based clustering (STRUCTURE). We showed that the cophenetic correlation coefficient is directly related to subgroup differentiation and can thus be used as an indicator of the presence of genetically distinct subgroups in germplasm collections. Whereas UPGMA performed well in preserving distances between accessions, Ward excelled in recovering groups. Our results also showed a close similarity between clusters obtained by Ward and by STRUCTURE. Traditional cluster analysis can provide an easy and effective way of determining structure in germplasm collections using molecular marker data, and, the output can be used for sampling core collections or for association studies.
尽管有更新的方法可用，但传统的层次聚类在植物遗传多样性研究中仍然非常流行。然而，对于其适用于分子标记数据的情况却知之甚少。我们使用真实和模拟的分子标记数据研究了传统层次聚类技术的性能。我们的研究还比较了传统层次聚类与基于模型的聚类（STRUCTURE）的性能。结果表明，聚合法系数与亚群分化直接相关，因此可以用作鉴定种质资源收集中存在遗传上不同亚群的指标。UPGMA 很好地保留了个体间的距离，而 Ward 则擅长于恢复群体。我们的结果还表明，Ward 和 STRUCTURE 获得的聚类之间非常相似。传统的聚类分析可以为使用分子标记数据确定种质资源收集中的结构提供一种简单有效的方法，其输出可用于采样核心收集或关联研究。
