Who is Who in Phylogenetic Networks

Publications of Kevin J. Liu     Order by:   Type | Year

Associated keywords

abstract-network evaluation explicit-network from-network from-rooted-trees from-sequences heuristic likelihood phylogenetic-network phylogeny Program-FastNet Program-PhyloNet Program-PhyloNet-HMM Program-PhyloNetworks-SNaQ reconstruction simulation unicyclic-network

Article (Journal)

1 Hussein A. Hejase and Kevin J. Liu. A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation. Vol. 17(422):1-12, 2016. Keywords: abstract network, evaluation, from sequences, phylogenetic network, phylogeny, Program PhyloNet, Program PhyloNetworks SNaQ, reconstruction, simulation, unicyclic network. Note: http://dx.doi.org/10.1186/s12859-016-1277-1.         2 Kevin J. Liu, Jingxuan Dai, Kathy Truong, Ying Song, Michael H. Kohn and Luay Nakhleh. An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes. In PLoS ONE, Vol. 10(6):e1003649, 2014. Keywords: explicit network, from network, phylogenetic network, phylogeny, Program PhyloNet-HMM. Note: http://arxiv.org/abs/1310.7989.         Toggle abstract "One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM-a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism. © 2014 Liu et al." 3 Yun Yu, Jianrong Dong, Kevin J. Liu and Luay Nakhleh. Maximum likelihood inference of reticulate evolutionary histories. In PNAS, Vol. 111(46):16448-16453, 2014. Keywords: explicit network, likelihood, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1073/pnas.1407950111.

InProceedings

4 Hussein A. Hejase, Natalie VandePol, Gregory A. Bonito and Kevin J. Liu. Fast and accurate statistical inference of phylogenetic networks using large-scale genomic sequence data. In RECOMB-CG18, Vol. 11183:242-259 of LNCS, Springer, 2018. Keywords: explicit network, from rooted trees, heuristic, phylogenetic network, phylogeny, Program FastNet, reconstruction. Note: http://biorxiv.org/content/early/2017/05/01/132795.