A novel expectation-maximization approach to infer general diploid selection from time-series genetic data

• Published in: PLoS genetics Vol. 21; no. 7; p. e1011769
• Main Authors: Fine, Adam G., Steinrücken, Matthias
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 22.07.2025; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Biology and Life Sciences; Computer Simulation; Diploidy; DNA sequencing; Earth Sciences; Genetic Variation; Genetics, Population - methods; Health aspects; Humans; Markov Chains; Markov processes; Models, Genetic; Nucleotide sequencing; Physical sciences; Population genetics; Selection, Genetic; United States

Detecting and quantifying the strength of selection is a major objective in population genetics. Since selection acts over multiple generations, many approaches have been developed to detect and quantify selection using genetic data sampled at multiple points in time. Such time-series genetic data i...