Performance of criteria for selecting evolutionary models in phylogenetics: a comprehensive study based on simulated datasets |
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| Authors: | Arong Luo Huijie Qiao Yanzhou Zhang Weifeng Shi Simon YW Ho Weijun Xu Aibing Zhang Chaodong Zhu |
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| Institution: | (1) Institute of Zoology, Chinese Academy of Sciences, 100101 Beijing, China;(2) Graduate University of Chinese Academy of Sciences, 100049 Beijing, China;(3) UCD Conway Institute of Biomolecular and Biomedical Sciences, University College Dublin, Dublin 4, Ireland;(4) Centre for Macroevolution and Macroecology, Research School of Biology, Australian National University, ACT 0200 Canberra, Australia;(5) School of Biological Sciences, University of Sydney, NSW 2006 Sydney, Australia;(6) Zhongbei College, Nanjing Normal University, 210046 Nanjing, China;(7) College of Life Sciences, Capital Normal University, 100048 Beijing, China |
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| Abstract: | Background Explicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly
used in phylogenetic studies of DNA sequence data. Appropriate selection of nucleotide substitution models is important because
the use of incorrect models can mislead phylogenetic inference. To better understand the performance of different model-selection
criteria, we used 33,600 simulated data sets to analyse the accuracy, precision, dissimilarity, and biases of the hierarchical
likelihood-ratio test, Akaike information criterion, Bayesian information criterion, and decision theory. |
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