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arXiv · 2012.09562

KwARG: Parsimonious reconstruction of ancestral recombination graphs with recurrent mutation

Anastasia Ignatieva·Rune B. Lyngsø·Paul A. Jenkins·Jotun Hein
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Abstract

The reconstruction of possible histories given a sample of genetic data in the presence of recombination and recurrent mutation is a challenging problem, but can provide key insights into the evolution of a population. We present KwARG, which implements a parsimony-based greedy heuristic algorithm for finding plausible genealogical histories (ancestral recombination graphs) that are minimal or near-minimal in the number of posited recombination and mutation events. Given an input dataset of aligned sequences, KwARG outputs a list of possible candidate solutions, each comprising a list of mutation and recombination events that could have generated the dataset; the relative proportion of recombinations and recurrent mutations in a solution can be controlled via specifying a set of 'cost' parameters. We demonstrate that the algorithm performs well when compared against existing methods. The software is made available on GitHub.

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Anastasia Ignatieva, Rune B. Lyngsø, Paul A. Jenkins, Jotun Hein. 2020-12-17. KwARG: Parsimonious reconstruction of ancestral recombination graphs with recurrent mutation. https://doi.org/10.1093/bioinformatics/btab351

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