Data from: The efficacy of consensus tree methods for summarising phylogenetic relationships from a posterior sample of trees estimated from morphological data

Hist_1000_CharsThe number of incorrect nodes found within each consensus subtracted from the number of correct nodes found tree within the same consensus trees constructed from 100 replicate matrices of 1000 morphological characters.Hist_10000_CharsThe number of incorrect nodes found within each consensus subtracted from the number of correct nodes found tree within the same consensus trees constructed from 100 replicate matrices of 10000 morphological characters.Mol_OnlyMajority rule (MRC), maximum a posteriori (MAP), and maximum clade credibility (MCC) consensus trees for Hymenoptera constructed from a posterior sample of trees obtained when only molecularl data was analysed.CombinedMajority rule (MRC), maximum a posteriori (MAP), and maximum clade credibility (MCC) consensus trees for Hymenoptera constructed from a posterior sample of trees obtained when both morphological and molecular data were analysed.BoxPlot_1000_CharsThe number and proportion of correct and incorrect clades presented in consensus trees constructed from 100 replicate matrices of 1000 simulated characters.BoxPlot_10000_CharsThe number and proportion of correct and incorrect clades presented in consensus trees constructed from 100 replicate matrices of 10000 simulated characters.Generator_treeTree used to simulate data

Hist_1000_Chars：针对基于100组重复的1000个形态学性状矩阵构建的每棵合意树（consensus tree），分别计算该树内正确节点数与错误节点数的差值。
Hist_10000_Chars：针对基于100组重复的10000个形态学性状矩阵构建的每棵合意树，分别计算该树内正确节点数与错误节点数的差值。
Mol_Only：该数据集包含基于仅使用分子数据（molecular data）分析得到的树后验样本构建的膜翅目（Hymenoptera）三类合意树：多数合意树（Majority rule consensus tree, MRC）、最大后验合意树（maximum a posteriori consensus tree, MAP）以及最大演化支可信度合意树（maximum clade credibility consensus tree, MCC）。
Combined：该数据集包含基于同时使用形态学与分子数据联合分析得到的树后验样本构建的膜翅目三类合意树：多数合意树（MRC）、最大后验合意树（MAP）以及最大演化支可信度合意树（MCC）。
BoxPlot_1000_Chars：该数据集统计基于100组重复的1000个模拟形态学性状矩阵构建的合意树中，正确演化支与错误演化支的数量及占比。
BoxPlot_10000_Chars：该数据集统计基于100组重复的10000个模拟形态学性状矩阵构建的合意树中，正确演化支与错误演化支的数量及占比。
Generator_tree：用于生成模拟数据的树。