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Species Tree Likelihood Computation Given SNP Data Using Ancestral Configurations

Fan, Hang
http://rave.ohiolink.edu/etdc/view?acc_num=osu1385995244

Abstract Details

2013, Doctor of Philosophy, Ohio State University, Statistics.
Inferring species trees given genetic data has been a challenge in the field of phylogenetics because of the high intensity during computation. In the coalescent framework, this dissertation proposes an innovative method of estimating the likelihood of a species tree directly from Single Nucleotide Polymorphism (SNP) data with a certain nucleotide substitution model. This method uses the idea of Ancestral Configurations (Wu, 2011) to avoid the computation burden brought by the enumeration of coalescent histories. Importance sampling is used to in Monte Carlo integration to approximate the expectations in the computation, where the accuracy of the approximation is tested in different tree models. The SNP data is processed beforehand which vastly boosts the efficiency of the method. Gene tree sampling given the species tree under the coalescent model is employed to make the computation feasible for large trees. Further, the branch lengths on the species tree are optimized according to the computed species tree likelihood, which provides the likelihood of the species tree topology given the SNP data. For inference, this likelihood computation method is implemented in the stepwise addition algorithm to infer the maximum likelihood species tree in the tree space given the SNP data, and simulations are conduced to test the performance. We also apply this method to the problem of species delimitation in the purpose of validating proposed species delimitations given the SNP data, and we run simulations to check the validation outcomes under different scenarios, such as in the presence of subsampling in the SNP data.
Laura Kubatko (Advisor)
Radu Herbei (Committee Member)
Bryan Carstens (Committee Member)
111 p.
Statistics
Species tree; likelihood; coalescent; ancestral configurations; SNP data

Recommended Citations

Citations

  • Fan, H. (2013). Species Tree Likelihood Computation Given SNP Data Using Ancestral Configurations [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385995244

    APA Style (7th edition)

  • Fan, Hang. Species Tree Likelihood Computation Given SNP Data Using Ancestral Configurations. 2013. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1385995244.

    MLA Style (8th edition)

  • Fan, Hang. "Species Tree Likelihood Computation Given SNP Data Using Ancestral Configurations." Doctoral dissertation, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1385995244

    Chicago Manual of Style (17th edition)

osu1385995244
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© 2013, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.