Fast Estimation of Recombination Rates Using Topological Data Analysis.

Genetics
Devon P HumphreysAndrew J Blumberg

Abstract

Accurate estimation of recombination rates is critical for studying the origins and maintenance of genetic diversity. Because the inference of recombination rates under a full evolutionary model is computationally expensive, we developed an alternative approach using topological data analysis (TDA) on genome sequences. We find that this method can analyze datasets larger than what can be handled by any existing recombination inference software, and has accuracy comparable to commonly used model-based methods with significantly less processing time. Previous TDA methods used information contained solely in the first Betti number ([Formula: see text]) of a set of genomes, which aims to capture the number of loops that can be detected within a genealogy. These explorations have proven difficult to connect to the theory of the underlying biological process of recombination, and, consequently, have unpredictable behavior under perturbations of the data. We introduce a new topological feature, which we call ψ, with a natural connection to coalescent models, and present novel arguments relating [Formula: see text] to population genetic models. Using simulations, we show that ψ and [Formula: see text] are differentially affected by mis...Continue Reading

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Citations

May 31, 2020·Nature Reviews. Genetics·Joshua V Peñalba, Jochen B W Wolf
Apr 5, 2020·Developmental Dynamics : an Official Publication of the American Association of Anatomists·Erik J AmézquitaDaniel H Chitwood
Feb 16, 2021·Molecular Biology and Evolution·Juan Ángel Patiño-GalindoRaul Rabadan
Jul 29, 2021·Bioinformatics·Ciara LoughreyAnna Jurek-Loughrey
Oct 10, 2021·Proceedings of the National Academy of Sciences of the United States of America·Oliver VipondHeather A Harrington

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