Prager E M, Wilson A C
J Mol Evol. 1978 Jun 20;11(2):129-42. doi: 10.1007/BF01733889.
The methods of Fitch and Margoliash and of Farris for the construction of phylogenetic trees were compared. A phenetic clustering technique--the UPGMA method--was also considered. The three methods were applied to difference matrices obtained from comparison of macromolecules by immunological, DNA hybridization, electrophoretic, and amino acid sequencing techniques. To evaluate the results, we used the goodness-of-fit criterion. In some instances, the F-M and Farris methods gave a comparably good fit of the output to the input data, though in most cases the F-M procedure gave a much better fit. By the fit criterion, the UPGMA procedure was on the average better than the Farris method but not as good as the F-M procedure. On the basis of the results given in this report and the goodness-of-fit criterion, it is suggested that where input data are likely to include overestimates as well as true estimates and underestimates of the actual distances between taxonomic units, the F-M method is the most reasonable to use for constructing phylogenies from distance matrices. Immunological, DNA hybridization, and electrophoretic data fall into this category. By contrast, where it is known that each input datum is indeed either a true estimate or an underestimate of the actual distance between 2 taxonomic units, the Farris procedure appears, on theoretical grounds, to be the matrix method of choice. Amino acid and nucleotide sequence data are in this category.
对费奇和马戈利亚什方法以及法里斯用于构建系统发育树的方法进行了比较。还考虑了一种表型聚类技术——非加权组平均法（UPGMA法）。这三种方法应用于通过免疫、DNA杂交、电泳和氨基酸测序技术比较大分子获得的差异矩阵。为了评估结果，我们使用了拟合优度标准。在某些情况下，费奇-马戈利亚什（F-M）方法和法里斯方法给出的输出与输入数据的拟合度相当好，不过在大多数情况下，F-M程序给出的拟合度要好得多。根据拟合标准，UPGMA程序平均比法里斯方法好，但不如F-M程序。根据本报告给出的结果和拟合优度标准，建议在输入数据可能既包括对分类单元之间实际距离的高估，也包括真实估计值和低估的情况下，F-M方法是从距离矩阵构建系统发育树最合理的方法。免疫、DNA杂交和电泳数据属于这一类。相比之下，在已知每个输入数据确实是对两个分类单元之间实际距离的真实估计值或低估的情况下，从理论上讲，法里斯程序似乎是首选的矩阵方法。氨基酸和核苷酸序列数据属于这一类。
