diplo-locus: A lightweight toolkit for inference and simulation of time-series genetic data under general diploid selection
Cheng, X.; Steinruecken, M.
Show 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 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.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Polaris: Polarization of ancestral and derived polymorphic alleles for inferences of extended haplotype homozygosity in human populations. 96%
- ipcoal: An interactive Python package for simulating and analyzing genealogies and sequences on a species tree or network 96%
- selscan 2.0: scanning for sweeps in unphased data 95%
Similar papers in this journal
- FGTpartitioner: A rapid method for parsimonious delimitation of ancestry breakpoints in large genome-wide SNP datasets 95%
- rTASSEL: an R interface to TASSEL for association mapping of complex traits 95%
- BREADR: An R Package for the Bayesian Estimation of Genetic Relatedness from Low-coverage Genotype Data 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.