Distance to the stochastic part of phylogenetic varieties. (May 2021)

• Record Type: Journal Article
• Authors: Casanellas, Marta; Fernández-Sánchez, Jesús; Garrote-López, Marina
• Is Part Of: Journal of symbolic computation. Volume 104(2021)
• Page Start: 653
• Page End: 682
• Publication Date: 2021-05
• Subjects: Phylogenetic variety -- Euclidean distance degree -- Semi-algebraic phylogenetics -- Group-based models -- Quartet topology -- Long-branch attraction; Mathematics -- Data processing -- Periodicals; Numerical analysis -- Data processing -- Periodicals; Automatic programming (Computer science) -- Periodicals; Mathématiques -- Informatique -- Périodiques; Analyse numérique -- Informatique -- Périodiques; Programmation automatique -- Périodiques; Automatic programming (Computer science); Mathematics -- Data processing; Numerical analysis -- Data processing; Periodicals; Electronic journals; 510.285
• DOI: 10.1016/j.jsc.2020.09.003
• Languages: English
• ISSNs: 0747-7171

Abstract

Abstract: Modelling the substitution of nucleotides along a phylogenetic tree is usually done by a hidden Markov process. This allows to define a distribution of characters at the leaves of the trees and one might be able to obtain polynomial relationships among the probabilities of different characters. The study of these polynomials and the geometry of the algebraic varieties defined by them can be used to reconstruct phylogenetic trees. However, not all points in these algebraic varieties have biological sense. In this paper, we explore the extent to which adding semi-algebraic conditions arising from the restriction to parameters with statistical meaning can improve existing methods of phylogenetic reconstruction. To this end, our aim is to compute the distance of data points to algebraic varieties and to the stochastic part of these varieties. Computing these distances involves optimization by nonlinear programming algorithms. We use analytical methods to find some of these distances for quartet trees evolving under the Kimura 3-parameter or the Jukes-Cantor models. Numerical algebraic geometry and computational algebra play also a fundamental role in this paper.