diplo-locus

diplo-locus simulates and performs inference from time-series genetic data under the Wright-Fisher diffusion with general diploid selection.

Key Features:

• Simulation: Simulates time-series genetic data under the Wright-Fisher diffusion with general diploid selection.
• Inference: Performs inference from time-series allele frequency data under the Wright-Fisher diffusion with general diploid selection.
• Python modules: Provides Python modules for programmatic access to simulation and inference functionality.
• Command-line tools: Includes command-line tools for large-scale empirical applications.

Scientific Applications:

• Ancient DNA analysis: Analyzes whole-genome time-series allele frequency data from ancient DNA sequences to elucidate dynamics of genetic variation under selection.
• Evolve-and-resequence experiments: Analyzes data from evolve-and-resequence experiments to infer parameters of selection models from allele frequency trajectories.
• Selection parameter inference: Infers parameters of selection models from allele frequency trajectories in large-scale empirical applications.

Methodology:

The tool implements the Wright-Fisher diffusion with general diploid selection for simulation and inference from time-series genetic data.