GSR: Simulator - pg-gan

Basic Package Attributes
AttributeValue
Title pg-gan
Short Description create realistic simulated data that matches real population genetic data.
Long Description This software can be used to create realistic simulated data that matches real population genetic data. It implements a GAN-based algorithm (Generative Adversarial Network).
Project Started 2021
Last Release 6 months, 3 weeks ago
Homepagehttps://github.com/mathiesonlab/pg-gan
Citations Wang Z, Wang J, Kourakos M, Hoang N, Lee HH, Mathieson I, Mathieson S, Automatic inference of demographic parameters using generative adversarial networks., Mol Ecol Resour, 03-20-2021 [ Abstract, cited in PMC ]
GSR Certification This simulator has not yet been evaluated for GSR Certification. Learn more about or request GSR Certification.
Author verificationThe basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator.
Detailed Attributes
Attribute CategoryAttribute
Target
Type of Simulated DataHaploid DNA Sequence,
VariationsBiallelic Marker,
Simulation MethodStandard Coalescent, Other,
Input
Data Type
File format
Output
Data Type
Sequencing Reads
File Format
Sample Type
Phenotype
Trait Type
Determinants
Evolutionary Features
Demographic
Population Size ChangesExponential Growth or Decline, User Defined,
Gene Flow
Spatiality
Life Cycle
Mating System
Fecundity
Natural Selection
Determinant
Models
Recombination
Mutation Models
Events Allowed
Other
InterfaceCommand-line,
Development
Tested PlatformsWindows, Mac OS X, Linux and Unix,
LanguagePython,
License
GSR Certification

No example publication using pg-gan has been provided.

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