Work

diplo-locus: a lightweight toolkit for inference and simulation of time-series genetic data under general diploid selection

Year: 2025

Type: article

Abstract: Whole-genome time-series allele frequency data are becoming more prevalent as ancient DNA sequences and data from evolve-and-resequence experiments are generated at a rapid pace. Such data present unprecedented opportunities to elucidate the dynamics of genetic variation under selection. However, despite many methods to infer parameters of selection models from allele frequency trajectories available in the literature, few provide user-friendly implementations for large-scale empirical applications. Here, we present diplo-locus, an open-source Python package that provides functionality to simulate and perform inference from time-series data under the Wright-Fisher diffusion with general diploid selection. The package includes Python modules as well as command-line tools and is available at: https://github.com/steinrue/diplo_locus.

Source: G3 Genes Genomes Genetics

DOI: 10.1093/g3journal/jkaf123

Authors: Xiaoheng Cheng, Matthias Steinrücken

Institution: University of Chicago

Language: English

Topic: Evolution and Genetic Dynamics

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,709

Funders: University of Chicago, National Institutes of Health, National Institute of General Medical Sciences