GSR: Simulator - GS

Basic Package Attributes
AttributeValue
Title GS
Short Description Generating samples for association studies based on HapMap data
Long Description A new version of gs is available. In addition to the functionalities implemented earlier, gs2.0 has implemented a comprehensive yet flexible model to simulate genetic and environmental interactions. The program can be used to generate samples in testing algorithms for tag SNP selection, haplotype inference, as well as epistatic detection.
Version 2.0
Last Release 16 years, 3 months ago
Homepagehttp://engr.case.edu/li_jing/gs.html
Citations Li J, Chen Y, Generating samples for association studies based on HapMap data., BMC Bioinformatics, 01-24-2008 [ Abstract, cited in PMC ]
GSR Certification This package has been evaluated. No certificates were awarded at this time.
Last evaluated05-15-2023 (334 days ago)
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 DataGenotype at Genetic Markers,
VariationsBiallelic Marker, Single Nucleotide Variation,
Simulation MethodResample Existing Data,
Input
Data Type
File format
Output
Data TypeGenotype or Sequence,
Sequencing Reads
File Format
Sample Type
Phenotype
Trait TypeQuantitative,
Determinants
Evolutionary Features
Demographic
Population Size Changes
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,
LanguageC or C++,
License
GSR Certification

Number of Primary Citations: 1

Number of Non-Primary Citations: 1

The following 1 publications are selected examples of applications that used GS.

2021

Guo Y, Wu C, Yuan Z, Wang Y, Liang Z, Wang Y, Zhang Y, Xu L, Gene-Based Testing of Interactions Using XGBoost in Genome-Wide Association Studies., Front Cell Dev Biol, 12-16-2021 [Abstract]


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