Python code for building and training a generative adversarial network for demographic inferences from genomic data
[This application is embargoed until January 1, 2025]. A collection of python and bash scripts to implement, train and deploy a generative adversarial network for population genetic inferences. The networks have been tuned to be deployed to genomic data from Anopheles mosquitoes. However, the general framework can be applied to other species. It requires the input data to be in Variant Call Format (VCF) format and the simulations need to be in msprime format. Full details about this application can be found at
https://doi.org/10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54
Default
Identification info
- Metadata Language
- English (en)
- Character set
- utf8
- Dataset Reference Date ()
- 2023-12-08
- Identifier
- doi: / 10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54
- Other citation details
- Pui, C.S., Fumagalli, M., Mathieson, S. (2023). Python code for building and training a generative adversarial network for demographic inferences from genomic data. NERC EDS Environmental Information Data Centre 10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54
- Limitations on Public Access
- otherRestrictions
- Other constraints
- Embargoed
- Use constraints
- otherRestrictions
- Use constraints
- otherRestrictions
- Other constraints
- If you reuse this data, you should cite: Pui, C.S., Fumagalli, M., Mathieson, S. (2023). Python code for building and training a generative adversarial network for demographic inferences from genomic data. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54
- Topic category
-
- Environment
Distribution Information
- Data format
-
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Python scripts
()
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Bash scripts
()
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R script
()
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Python scripts
()
- Quality Scope
- application
- Other
- application
Report
- Dataset Reference Date ()
- 2010-12-08
- Statement
- The methodology can be applied to up to two populations at the same time. The code uses the keras python package and the scripts have been tested via simulations. Inferences were tested using simulations with known output, and the power to infer the ground truth was recovered. Simulations can be performed using msprime or SLiM.
Metadata
- File identifier
- 3ae572f6-4862-47ae-b4a0-4b9c496b5b54 XML
- Metadata Language
- English (en)
- Character set
- ISO/IEC 8859-1 (also known as Latin 1)
- Resource type
- application
- Hierarchy level name
- application
- Metadata Date
- 2024-02-08T17:25:18
- Metadata standard name
- UK GEMINI
- Metadata standard version
- 2.3
NERC EDS Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg
,
Lancaster
,
LA1 4AP
,
UK
https://eidc.ac.uk/