IntroUNET: Identifying introgressed alleles via semantic segmentation.

ABSTRACT: A growing body of evidence suggests that gene flow between closely related species is a widespread phenomenon. Alleles that introgress from one species into a close relative are typically neutral or deleterious, but sometimes confer a significant fitness advantage. Given the potential relevance to speciation and adaptation, numerous methods have therefore been devised to identify regions of the genome that have experienced introgression. Recently, supervised machine learning approaches have been shown to be highly effective for detecting introgression. One especially promising approach is to treat population genetic inference as an image classification problem, and feed an image representation of a population genetic alignment as input to a deep neural network that distinguishes among evol

SUBMITTER: Ray DD 

PROVIDER: S-EPMC10906877 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature