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Published on: December 7, 2021
diplo-locus: A lightweight toolkit for inference and simulation of time-series genetic data under general diploid
Xiaoheng Cheng1, Matthias Steinrücken1,2
1Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
Abstract:
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 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.
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