A Birth-Death-Migration Model for Alignment Free Phylogeny Estimation usingk-mer Frequencies

Abstract

AbstractEstimating phylogenetic trees from molecular data is an important challenge in bioinformatics and evolutionary biology. A widely used approach is to first perform a multiple sequence alignment and then to find a tree that maximizes likelihood computed under a model of nucleotide substitution. However, sequence alignment is computationally challenging for long sequences, especially in the presence of genomic rearrangements. To address this, methods of constructing phylogenetic trees without aligning the sequences i.e. alignment free methods have been proposed. They are generally fast and can be used to construct phylogenetic trees of a large number of species but they primarily estimate phylogenies by computing pairwise distances and are not based on any statistical model of molecular evolution. In this paper, we introduce a model fork-mer frequency change based on a birth-death-migration process which can be used to estimate maximum likelihood phylogenies fromk-mer frequencies in an alignment free approach.