STATISTICAL PROPERTIES OF THE ORDINARY LEAST-SQUARES, GENERALIZED LEAST-SQUARES, AND MINIMUM-EVOLUTION METHODS OF PHYLOGENETIC INFERENCE
STATISTICAL PROPERTIES OF THE ORDINARY LEAST-SQUARES, GENERALIZED LEAST-SQUARES, AND MINIMUM-EVOLUTION METHODS OF PHYLOGENETIC INFERENCE
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DOI：
10.1007/bf00161174
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发表时间：
1992-10-01
影响因子：
3.9
通讯作者：
NEI, M
中科院分区：
文献类型：
--
作者：
RZHETSKY, A;NEI, M
通过考虑四个DNA序列的情况，研究了系统发育推断的普通最小二乘（OLS），广义最小二乘（GLS）和最小进化（ME）方法的统计特性。分析研究表明，所有三种方法在统计学上是一致的，因为随着所检测的核苷酸数量（m）的增加，只要所使用的进化距离是无偏的，它们倾向于选择真正的树。然而，当进化距离（d（ij）的）是大的，研究中的序列不是很长，OLS标准往往是有偏见的，可能会选择一个不正确的树下随机选择比预期更频繁。当d（ij）趋近于零时，d（ij）的方差-协方差矩阵变为奇异，因此当d（ij）较小时，GLS可能不适用. ME方法不存在这些问题，并且ME准则是统计无偏的。计算机模拟表明，ME方法在获得真树方面比OLS和GLS方法更有效，并且当d（ij）小时，OLS比GLS更有效，但在其他情况下，GLS更有效。
Statistical properties of the ordinary least-squares (OLS), generalized least-squares (GLS), and minimum-evolution (ME) methods of phylogenetic inference were studied by considering the case of four DNA sequences. Analytical study has shown that all three methods are statistically consistent in the sense that as the number of nucleotides examined (m) increases they tend to choose the true tree as long as the evolutionary distances used are unbiased. When evolutionary distances (d(ij)'s) are large and sequences under study are not very long, however, the OLS criterion is often biased and may choose an incorrect tree more often than expected under random choice. It is also shown that the variance-covariance matrix of d(ij);'s becomes singular as d(ij)'s approach zero and thus the GLS may not be applicable when d(ij)'s are small. The ME method suffers from neither of these problems, and the ME criterion is statistically unbiased. Computer simulation has shown that the ME method is more efficient in obtaining the true tree than the OLS and GLS methods and that the OLS is more efficient than the GLS when d(ij)'s are small, but otherwise the GLS is more efficient.