Identifying model violations under the multispecies coalescent model using P2C2M.SNAPP
Identifying model violations under the multispecies coalescent model using P2C2M.SNAPP
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DOI：
10.7717/peerj.8271
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发表时间：
2020-01-10
期刊：
影响因子：
2.7
通讯作者：
Carstens, Bryan C.
中科院分区：
文献类型：
--
作者：
Duckett, Drew J.;Pelletier, Tara A.;Carstens, Bryan C.
在多物种聚结模型（MSCM）下的系统发育估计假设所有位点之间的不一致都是由于谱系分类不完全造成的。因此，将MSCM应用于包含由其他过程（如基因流）引起的不一致的数据集，可能导致系统发育估计有偏差。为了识别使用MSCM时可能存在的偏差，我们提出了P2C2M.SNAPP。P2C2M。SNAPP是一个R包，它使用后验预测模拟来识别模型违规。P2C2M。SNAPP利用SNAPP软件包输出的物种树的后验分布来模拟MSCM下的后验预测数据集，然后利用汇总统计将经验数据或后验分布与后验预测分布进行比较，以识别模型违规。在模拟测试中，P2C2M。SNAPP正确分类了高达83%的数据集（取决于所使用的汇总统计），以确定它们是否违反了MSCM模型。P2C2M。SNAPP代表了一种用户友好的方式，供研究人员在使用流行的SNAPP系统发育估计程序时执行后验预测模型检查。它是一个免费的R包，还有额外的程序细节和教程。
Phylogenetic estimation under the multispecies coalescent model (MSCM) assumes all incongruence among loci is caused by incomplete lineage sorting. Therefore, applying the MSCM to datasets that contain incongruence that is caused by other processes, such as gene flow, can lead to biased phylogeny estimates. To identify possible bias when using the MSCM, we present P2C2M.SNAPP. P2C2M.SNAPP is an R package that identifies model violations using posterior predictive simulation. P2C2M.SNAPP uses the posterior distribution of species trees output by the software package SNAPP to simulate posterior predictive datasets under the MSCM, and then uses summary statistics to compare either the empirical data or the posterior distribution to the posterior predictive distribution to identify model violations. In simulation testing, P2C2M.SNAPP correctly classified up to 83% of datasets (depending on the summary statistic used) as to whether or not they violated the MSCM model. P2C2M.SNAPP represents a user-friendly way for researchers to perform posterior predictive model checks when using the popular SNAPP phylogenetic estimation program. It is freely available as an R package, along with additional program details and tutorials.