SPLATCHE3

SPLATCHE3 simulates genetic data under spatially explicit evolutionary scenarios to model migration, hybridization, temporal sampling, and DNA mutation processes for population genetics studies.


Key Features:

  • Long-Distance Migration: Simulates long-distance migration events to assess gene flow across large geographical scales.
  • Heterogeneous Migrations: Supports spatially and temporally heterogeneous short-scale migrations to model complex, variable migration patterns.
  • Hybridization Models: Simulates alternative hybridization scenarios to evaluate genetic outcomes of interbreeding between populations or species.
  • Serial Sample Simulation: Simulates serial samples of genetic data to study temporal changes in genetic structure and diversity.
  • DNA Mutation Models: Implements a wide variety of DNA mutation models to represent different mutational processes and rates.

Scientific Applications:

  • Migration and Diversity Analysis: Investigating the effects of migration on genetic diversity across geographic space.
  • Hybridization Studies: Studying hybridization events and their impact on population genetic composition.
  • Temporal Genetic Change: Analyzing temporal changes in genetic data using serially sampled datasets.
  • Mutation Pattern Modeling: Modeling evolutionary scenarios with varying mutation rates and mutational patterns.

Methodology:

Operates under a spatially explicit framework that models the geographical distribution of populations when simulating evolutionary scenarios, including migration, hybridization, serial sampling, and DNA mutation processes.

Topics

Details

License:
Unlicense
Maturity:
Mature
Cost:
Free of charge
Tool Type:
command-line tool, desktop application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
C++
Added:
8/9/2019
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Modelling and simulation

Publications

Currat M, Arenas M, Quilodràn CS, Excoffier L, Ray N. SPLATCHE3: simulation of serial genetic data under spatially explicit evolutionary scenarios including long-distance dispersal. Bioinformatics. 2019;35(21):4480-4483. doi:10.1093/bioinformatics/btz311. PMID:31077292. PMCID:PMC6821363.

PMID: 31077292
PMCID: PMC6821363
Funding: - Swiss National Science Foundation: 31003A_156853, 31003A_182577 - Spanish Government: ED431F 2018/08, RYC-2015-18241

Documentation