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ABSTRACT: Summary
Whole-genome time-series allele frequency data are becoming more prevalent as ancient DNA (aDNA) sequences and data from evolve-and-resequence (E&R) experiments are generated at a rapid pace. Such data presents unprecedented opportunities to elucidate the dynamics of adaptative genetic variation. 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 under the Wright-Fisher diffusion with general diploid selection. The package includes Python modules as well as command-line tools.Availability
Python package and command-line tool avilable at: https://github.com/steinrue/diplo_locus or https://pypi.org/project/diplo-locus/.
SUBMITTER: Cheng X
PROVIDER: S-EPMC10614779 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Cheng Xiaoheng X Steinrücken Matthias M
bioRxiv : the preprint server for biology 20250526
Whole-genome time-series allele frequency data are becoming more prevalent as ancient DNA (aDNA) sequences and data from evolve-and-resequence (E&R) experiments are generated at a rapid pace. Such data presents 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 userfriendly implementations for large-scale empiri ...[more]