@ARTICLE{TreeBASE2Ref16558, author = {David C. Marshall and Chris Simon and Thomas R. Buckley}, title = {Accurate Branch Length Estimation in Partitioned Bayesian Analyses Requires Accommodation of Among-Partition Rate Variation and Attention to Branch Length Priors.}, year = {2006}, keywords = {}, doi = {10.1080/10635150601087641}, url = {}, pmid = {}, journal = {Systematic Biology}, volume = {55}, number = {6}, pages = {993--1003}, abstract = {Molecular phylogenetic studies are making increasing use of partitioned Bayesian analyses via software tools like MrBayes version 3. Data partitioning is important because, as long as the same topology/history underlies all of the partitions, it addresses some of the problems associated with the combination of data sets with heterogeneous rates and eliminates the need to argue the validity of tests that have been used to judge data combinability. In addition, new studies indicate that data partitioning and the use of mixed models often dramatically improve the fit of model to data without the cost of overparameterization. While applying partitioned models to studies of protein-coding mitochondrial data, we have found that analyses using MrBayes may infer overly ?long? trees if among-partition rate variation (APRV) is not explicitly accommodated and if data from different partitions evolve at different average rates.} }

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