GSR: Simulator - FREGENE

Basic Package Attributes
Short Description FREGENE is a C++ program that simulates sequence-like data over large genomic regions in large diploid populations.
Long Description FREGENE works forwards-in-time which allows a wide range of demographic and selection scenarios to be implemented. Many such models are already incorporated into FREGENE, and since it is open source users can modify or extend these. Coalescent methods have difficulty incorporating large amounts of gene conversion or crossover (Hoggart et al. 2007), whereas these pose no particular problem for FREGENE. FREGENE offers a flexible model for recombination hotspots, and can readily simulate regions up to tens of Mb on a standard desktop computer. The principle limitation of forward-in-time algorithms is computational, since the entire population must be tracked through time, not only the chromosomes that are ancestral to the observed sample. FREGENE implements many features to enhance computational efficiency, and includes a rescaling option that greatly reduces computation time at the cost of some approximation.
Project Started 2007
Last Release 12 years, 2 months ago
Citations Chadeau-Hyam M, Hoggart CJ, O'Reilly PF, Whittaker JC, De Iorio M, Balding DJ, Fregene: simulation of realistic sequence-level data in populations and ascertained samples., BMC Bioinformatics, 09-08-2008 [ Abstract, cited in PMC ]
GSR Certification


Last evaluated05-03-2018 (897 days ago)
Detailed Attributes
Attribute CategoryAttribute
Type of Simulated DataDiploid DNA Sequence, Haploid DNA Sequence,
VariationsBiallelic Marker, Single Nucleotide Variation,
Simulation MethodForward-time,
Data Type
File formatXML,
Data TypeGenotype or Sequence, Demographic, Mutation, Diversity Measures,
Sequencing Reads
File FormatOther,
Sample TypeRandom or Independent, Case-control,
Trait Type
Evolutionary Features
Population Size ChangesConstant Size, Exponential Growth or Decline, User Defined,
Gene FlowIsland Models, User-defined Matrix,
Life CycleDiscrete Generation Model,
Mating System
Natural Selection
DeterminantSingle-locus, Multi-locus,
ModelsBalancing Selection, Multi-locus models, Random Fitness Effects,
RecombinationUniform, Varying Recombination Rates, Gene Conversion Allowed,
Mutation ModelsTwo-allele Mutation Model (Symmetric),
Events Allowed
Tested PlatformsMac OS X, Linux and Unix, Solaris,
LanguageC or C++,
LicenseGNU Public License,
GSR CertificationAccessibility, Documentation,

The following 10 publications are selected examples of applications that used FREGENE.


Cule E, De Iorio M, Ridge regression in prediction problems: automatic choice of the ridge parameter., Genet Epidemiol, 11-01-2013 [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]


Keller MC, Visscher PM, Goddard ME, Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data., Genetics, 09-01-2011 [Abstract]

Cule E, Vineis P, De Iorio M, Significance testing in ridge regression for genetic data., BMC Bioinformatics, 09-19-2011 [Abstract]

Howrigan DP, Simonson MA, Keller MC, Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms., BMC Genomics, 09-23-2011 [Abstract]

Lipman PJ, Yip WK, AlChawa T, Ludwig KU, Mangold E, Lange C, On the analysis of sequence data: testing for disease susceptibility loci using patterns of linkage disequilibrium., Genet Epidemiol, 12-01-2011 [Abstract]

Bouaziz M, Ambroise C, Guedj M, Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies., PLoS One, 01-01-2011 [Abstract]


Enard D, Depaulis F, Roest Crollius H, Human and non-human primate genomes share hotspots of positive selection., PLoS Genet, 02-05-2010 [Abstract]

Powell JE, Visscher PM, Goddard ME, Reconciling the analysis of IBD and IBS in complex trait studies., Nat Rev Genet, 11-01-2010 [Abstract]

Ayers KL, Cordell HJ, SNP selection in genome-wide and candidate gene studies via penalized logistic regression., Genet Epidemiol, 12-01-2010 [Abstract]

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