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ML runs were performed for 1000 bootstrap iterations under the GTR model of sequence evolution with two parameters for the number of categories defined by a gamma distribution and the CAT approximation.
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The robustness of each tree component was accessed by 500 non-parametric bootstrap iterations with the phyml program under the WAG+Γ+I model of protein evolution.
Bootstrap iterations to assess the robustness of the generated trees were decided automatically by RAxML.
The phylogram represents a consensus tree based on 100 bootstrap iterations, calculated by the Minimum Evolution method under default parameters [66].
The error rate of the model is based on the combined error rate of all the bootstrap iterations when the data not included in that iteration is predicted using the tree from the current iteration.
The default number of bootstrap iterations is 10,000, while the maximum is 100,000.
Finally, by incorporating the multi-model inference into each bootstrap iteration, the method also accounts for the uncertainty due to uncertainty in model selection.
Using class discovery under correlation distance and Euclidean distance metrics, 10,000 bootstrap iterations were performed to assess the significance of the observed clusters using the pvclust package for R[ 25].
Each bootstrap iteration included both the cost and survival of the matched pair.
The tree was evaluated statistically using 1000 bootstrap iterations and was visualized using the 'NJplot' tool [ 47].
Typically this entails an additional factor of 100 1000 or more in the running time owing to the bootstrap iterations.
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