slendr: A Simulation Framework for Spatiotemporal Population Genetics
In bodkan/spannr: A Simulation Framework for Spatiotemporal Population Genetics
slendr R Documentation
A Simulation Framework for Spatiotemporal Population Genetics
Description
A framework for simulating spatially explicit genomic data which
leverages real cartographic information for programmatic and visual encoding
of spatiotemporal population dynamics on real geographic landscapes. Population
genetic models are then automatically executed by the 'SLiM' software behind
the scenes, using a custom built-in simulation 'SLiM' script. Additionally,
fully abstract spatial models not tied to a specific geographic location are
supported, and users can also simulate data from standard, non-spatial,
random-mating models. These can be simulated either with the 'SLiM' built-in
back-end script, or using an efficient coalescent population genetics simulator
'msprime' with a custom-built 'Python' script bundled with the R package.
Simulated genomic data is saved in a tree-sequence format and can be loaded,
manipulated, and summarised using tree-sequence functionality via an R
interface to the 'Python' module 'tskit'. Complete model configuration,
simulation and analysis pipelines can be therefore constructed without
a need to leave the R environment, eliminating friction between disparate
tools for population genetic simulations and data analysis.
Details
You can find installation instructions, reference manual, and tutorials at
https://www.slendr.net.
Author(s)
Maintainer: Martin Petr contact@bodkan.net (ORCID)
See Also
Useful links:
bodkan/spannr documentation built on Dec. 19, 2024, 11:43 p.m.
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| slendr | R Documentation |
A Simulation Framework for Spatiotemporal Population Genetics
Description
A framework for simulating spatially explicit genomic data which leverages real cartographic information for programmatic and visual encoding of spatiotemporal population dynamics on real geographic landscapes. Population genetic models are then automatically executed by the 'SLiM' software behind the scenes, using a custom built-in simulation 'SLiM' script. Additionally, fully abstract spatial models not tied to a specific geographic location are supported, and users can also simulate data from standard, non-spatial, random-mating models. These can be simulated either with the 'SLiM' built-in back-end script, or using an efficient coalescent population genetics simulator 'msprime' with a custom-built 'Python' script bundled with the R package. Simulated genomic data is saved in a tree-sequence format and can be loaded, manipulated, and summarised using tree-sequence functionality via an R interface to the 'Python' module 'tskit'. Complete model configuration, simulation and analysis pipelines can be therefore constructed without a need to leave the R environment, eliminating friction between disparate tools for population genetic simulations and data analysis.
Details
You can find installation instructions, reference manual, and tutorials at https://www.slendr.net.
Author(s)
Maintainer: Martin Petr contact@bodkan.net (ORCID)
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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