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Simon Joly. JML: Testing hybridization from species trees. In Molecular Ecology Ressources, Vol. 12(1):179-184, 2012. Keywords: from species tree, hybridization, lineage sorting, phylogenetic network, phylogeny, Program JML, statistical model. Note: http://www.plantevolution.org/pdf/JMLpaper_accepted.pdf.
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"I introduce the software jml that tests for the presence of hybridization in multispecies sequence data sets by posterior predictive checking following Joly, McLenachan and Lockhart (2009, American Naturalist e54). Although their method could potentially be applied on any data set, the lack of appropriate software made its application difficult. The software jml thus fills a need for an easy application of the method but also includes improvements such as the possibility to incorporate uncertainty in the species tree topology. The jml software uses a posterior distribution of species trees, population sizes and branch lengths to simulate replicate sequence data sets using the coalescent with no migration. A test quantity, defined as the minimum pairwise sequence distance between sequences of two species, is then evaluated on the simulated data sets and compared to the one estimated from the original data. Because the test quantity is a good predictor of hybridization events, departure from the bifurcating species tree model could be interpreted as evidence of hybridization. Software performance in terms of computing time is evaluated for several parameters. I also show an application example of the software for detecting hybridization among native diploid North American roses. © 2011 Blackwell Publishing Ltd."
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Simon Joly,
Patricia A. McLenachan and
Peter J. Lockhart. A Statistical Approach for Distinguishing Hybridization and Incomplete Lineage Sorting. In The American Naturalist, Vol. 174(2):E54-E70, 2009. Keywords: hybridization, lineage sorting, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://www.plantevolution.org/pdf/Joly&al_2009_AmNat.pdf.
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"The extent and evolutionary significance of hybridization is difficult to evaluate because of the difficulty in distinguishing hybridization from incomplete lineage sorting. Here we present a novel parametric approach for statistically distinguishing hybridization from incomplete lineage sorting based on minimum genetic distances of a nonrecombining locus. It is based on the idea that the expected minimum genetic distance between sequences from two species is smaller for some hybridization events than for incomplete lineage sorting scenarios. When applied to empirical data sets, distributions can be generated for the minimum interspecies distances expected under incomplete lineage sorting using coalescent simulations. If the observed distance between sequences from two species is smaller than its predicted distribution, incomplete lineage sorting can be rejected and hybridization inferred. We demonstrate the power of the method using simulations and illustrate its application on New Zealand alpine buttercups (Ranunculus). The method is robust and complements existing approaches. Thus it should allow biologists to assess with greater accuracy the importance of hybridization in evolution. © 2009 by The University of Chicago."
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