GSR: Simulator - simuGWAS

Basic Package Attributes
AttributeValue
Title simuGWAS
Short Description A forward-time simulator that simulates realistic samples for genome-wide association studies.
Long Description simuGWAS evolves a population forward in time, subject to rapid population expansion, mutation, recombination and natural selection. A trajectory simulation method is used to control the allele frequency of optional disease predisposing loci. A scaling approach can be used to improve efficiency when weak, additive genetic factors are used.
Version 1.0
Project Started 2009
Last Release 10 years ago
Homepagehttps://github.com/BoPeng/simuPOP-examples/tree/master/published/simuGWAS
Citations Peng B, Amos CI, Forward-time simulation of realistic samples for genome-wide association studies., BMC Bioinformatics, 09-01-2010 [ Abstract, cited in PMC ]
GSR Certification

Accessibility
Documentation
Application
Support

Last evaluated03-28-2020 (203 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,
Simulation MethodForward-time,
Input
Data TypeEmpirical (Hapmap 2 or 3), Other (List of markers (optional)),
File format
Output
Data TypeGenotype or Sequence, Phenotypic Trait,
Sequencing Reads
File FormatProgram Specific (A simupop population),
Sample TypeRandom or Independent, Sibpairs, Trios and Nuclear Families, Case-control,
Phenotype
Trait Type
DeterminantsSingle Genetic Marker, Multiple Genetic Markers, Gene-Gene Interaction,
Evolutionary Features
Demographic
Population Size ChangesConstant Size, Exponential Growth or Decline,
Gene FlowStepping Stone Models, Admixed Population,
Spatiality
Life CycleDiscrete Generation Model,
Mating SystemRandom Mating,
FecundityConstant Number,
Natural Selection
DeterminantSingle-locus, Multi-locus,
ModelsDirectional Selection, Balancing Selection, Multi-locus models, Epistasis,
RecombinationUniform (Proportional to marker distance),
Mutation ModelsTwo-allele Mutation Model,
Events Allowed
Other
InterfaceCommand-line, Graphical User Interface, Script-based,
Development
Tested PlatformsWindows, Mac OS X, Linux and Unix, Solaris,
LanguagePython (Simupop),
LicenseGNU Public License,
GSR CertificationAccessibility, Documentation, Support,

The following 6 publications are selected examples of applications that used simuGWAS.

2019

Dimitromanolakis A, Paterson AD, Sun L, Fast and Accurate Shared Segment Detection and Relatedness Estimation in Un-phased Genetic Data via TRUFFLE., Am J Hum Genet, 07-03-2019 [Abstract]

Dimitromanolakis A, Paterson AD, Sun L, Fast and Accurate Shared Segment Detection and Relatedness Estimation in Un-phased Genetic Data via TRUFFLE., Am J Hum Genet, 07-03-2019 [Abstract]

2013

Sim A, Tsagkrasoulis D, Montana G, Random forests on distance matrices for imaging genetics studies., Stat Appl Genet Mol Biol, 12-01-2013 [Abstract]

2012

Brown MD, Glazner CG, Zheng C, Thompson EA, Inferring coancestry in population samples in the presence of linkage disequilibrium., Genetics, 04-01-2012 [Abstract]

Wang Y, Gjuvsland AB, Vik JO, Smith NP, Hunter PJ, Omholt SW, Parameters in dynamic models of complex traits are containers of missing heritability., PLoS Comput Biol, 01-01-2012 [Abstract]

Bouaziz M, Paccard C, Guedj M, Ambroise C, SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies., PLoS One, 01-01-2012 [Abstract]


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