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Nevin Manimala Statistics

Quartet-Based Inference is Statistically Consistent Under the Unified Duplication-Loss-Coalescence Model

Bioinformatics. 2021 May 28:btab414. doi: 10.1093/bioinformatics/btab414. Online ahead of print.

ABSTRACT

MOTIVATION: The classic multispecies coalescent (MSC) model provides the means for theoretical justification of incomplete lineage sorting-aware species tree inference methods. This has motivated an extensive body of work on phylogenetic methods that are statistically consistent under MSC. One such particularly popular method is ASTRAL, a quartet-based species tree inference method. Novel studies suggest that ASTRAL also performs well when given multi-locus gene trees in simulation studies. Further, Legried et al. recently demonstrated that ASTRAL is statistically consistent under the gene duplication and loss model (GDL). GDL is prevalent in evolutionary histories and is the first core process in the powerful duplication-loss-coalescence evolutionary model (DLCoal) by Rasmussen and Kellis.

RESULTS: In this work we prove that ASTRAL is statistically consistent under the general DLCoal model. Therefore, our result supports the empirical evidence from the simulation-based studies. More broadly, we prove that the quartet-based inference approach is statistically consistent under DLCoal.

PMID:34048529 | DOI:10.1093/bioinformatics/btab414

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