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A Simulation Study to Examine the Information Content in Phylogenomic Data Sets under the Multispecies Coalescent Model
Author(s) -
Jun Huang,
Tomáš Flouri,
Ziheng Yang
Publication year - 2020
Publication title -
molecular biology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.637
H-Index - 218
eISSN - 1537-1719
pISSN - 0737-4038
DOI - 10.1093/molbev/msaa166
Subject(s) - coalescent theory , biology , inference , mutation rate , divergence (linguistics) , evolutionary biology , introgression , bayes' theorem , tree (set theory) , bayesian probability , estimation , bayesian inference , effective population size , approximate bayesian computation , statistics , phylogenetic tree , genetics , artificial intelligence , mathematics , computer science , genetic variation , gene , mathematical analysis , linguistics , philosophy , management , economics
We use computer simulation to examine the information content in multilocus data sets for inference under the multispecies coalescent model. Inference problems considered include estimation of evolutionary parameters (such as species divergence times, population sizes, and cross-species introgression probabilities), species tree estimation, and species delimitation based on Bayesian comparison of delimitation models. We found that the number of loci is the most influential factor for almost all inference problems examined. Although the number of sequences per species does not appear to be important to species tree estimation, it is very influential to species delimitation. Increasing the number of sites and the per-site mutation rate both increase the mutation rate for the whole locus and these have the same effect on estimation of parameters, but the sequence length has a greater effect than the per-site mutation rate for species tree estimation. We discuss the computational costs when the data size increases and provide guidelines concerning the subsampling of genomic data to enable the application of full-likelihood methods of inference.

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