Freudenstein John V, Davis Jerrold I
Department of Evolution, Ecology and Organismal Biology, Ohio State University Herbarium, 1315 Kinnear Road, Columbus, OH 43212, USA.
L.H. Bailey Hortorium and Department of Plant Biology, Cornell University, 412 Mann Library, Ithaca, NY 14853, USA.
Cladistics. 2010 Dec;26(6):643-656. doi: 10.1111/j.1096-0031.2010.00304.x.
The success of resampling approaches to branch support depends on the effectiveness of the underlying tree searches. Two primary factors are identified as key: the depth of tree search and the number of trees saved per resampling replicate. Two datasets were explored for a range of search parameters using jackknifing. Greater depth of tree search tends to increase support values because shorter trees conflict less with each other, while increasing numbers of trees saved tends to reduce support values because of conflict that reduces structure in the replicate consensus. Although a relatively small amount of branch swapping will achieve near-accurate values for a majority of clades, some clades do not yield accurate values until more extensive searches are performed. This means that in order to maximize the accuracy of resampling analyses, one should employ as extensive a search strategy as possible, and save as many trees per replicate as possible. Strict consensus summary of resampling replicates is preferable to frequency-within-replicates summary because it is a more conservative approach to the reporting of replicate results. Jackknife analysis is preferable to bootstrap because of its closer relationship to the original data.© The Willi Hennig Society 2010.
重抽样方法对分支支持度的成功取决于基础树搜索的有效性。确定了两个关键的主要因素:树搜索的深度以及每个重抽样重复保存的树的数量。使用刀切法针对一系列搜索参数对两个数据集进行了探索。树搜索深度越大往往会增加支持值,因为较短的树相互之间冲突较少,而保存的树的数量增加往往会降低支持值,这是由于冲突会减少重复一致中的结构。尽管相对少量的分支交换就能为大多数分支类群获得接近准确的值,但有些分支类群在进行更广泛的搜索之前不会产生准确的值。这意味着为了使重抽样分析的准确性最大化,应该采用尽可能广泛的搜索策略,并在每个重复中保存尽可能多的树。重抽样重复的严格合意总结比分重复内频率总结更可取,因为它是报告重复结果时更保守的方法。刀切法分析比自展法更可取,因为它与原始数据的关系更紧密。© 威利·亨尼希学会2010年。