Algorithms for MDC-Based Multi-Locus Phylogeny Inference: Beyond Rooted Binary Gene Trees on Single Alleles

被引:50
|
作者
Yu, Yun [1 ]
Warnow, Tandy [2 ]
Nakhleh, Luay [1 ,2 ]
机构
[1] Rice Univ, Dept Comp Sci, Houston, TX 77005 USA
[2] Univ Texas Austin, Dept Comp Sci, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
algorithms; coalescence; dynamic programming; graph theory; phylogenetic trees; SPECIES TREES; MAXIMUM-LIKELIHOOD; DISTRIBUTIONS; INCONGRUENCE; PROBABILITY;
D O I
10.1089/cmb.2011.0174
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is Minimize Deep Coalescence (MDC). Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this article, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rooted/non-binary, and unrooted/non-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. In addition, we devise MDC-based algorithms for cases when multiple alleles per species may be sampled. We study the performance of these methods in coalescent-based computer simulations.
引用
收藏
页码:1543 / 1559
页数:17
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