Rescuing concatenation with maximum likelihood using supermatrix rooted triples

Author: DeGiorgio, M.; Degnan, J.H.

Date: 2009

Publisher: University of Canterbury. Mathematics and Statistics

Type: Conference poster

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Concatenated alignments are often used to infer species-level reslationships. Previous studies have shown that analysis of concatenated alignments using maximum likelihood (ML) can produce misleading results. We develop a polynomial-time method that constructs a species tree through inferred rooted triples from concatenated alignments. We call this method SuperMatrix Rooted Triple (SMRT). We show that SMRT performs well in simulations and then show that it is a statistically consistent estimator of a clocklike species tree under a binary substitution model as well as other assumptions. SMRT is therefore a computationally efficient and statistically consistent estimator of species trees.

Subjects: Mathematical Sciences, Mathematics, Mathematical logic, set theory, lattices and combinatorics, Other Mathematical Sciences, Biological Mathematics, Biological Sciences, Genetics, Genetics not elsewhere classified

Marsden Codes: 230000, 230100, 230101, 239900, 239901, 270000, 270200, 270299

Citation: ["DeGiorgio, M., Degnan, J.H. (2009) Rescuing concatenation with maximum likelihood using supermatrix rooted triples. Philadelphia, PA, USA: 9th Workshop on Algorithms in Bioinformatics (WABI 2009), 12-13 Sep 2009."]