GSR: Simulator - QMSim

Basic Package Attributes
Title QMSim
Short Description QTL and Marker Simulator
Long Description Linkage disequilibrium (LD) and linkage analyses have been used extensively to identify quantitative trait loci (QTL) in human and livestock. Owing to the recent developments in genotyping technologies, dense marker maps are now available for several livestock species. Even though genotyping costs have substantially declined, large scale genome-wide association studies are still costly. For this reason many studies in livestock suffer from small sample size or from low density of markers. However, simulation is a highly valuable tool for assessing and validating new proposed methods for association studies at very low cost. During the last few decades, simulation has played a major role in answering a wide variety of questions in genomics. Several software have been developed for simulating genomes especially in human research. However most of the developed software tools do not provide functionality required for many of the applications in livestock. QMSim was developed to simulate large scale genomic data in livestock populations. QMSim is a family based simulator, which can also take into account predefined evolutionary features, such as LD, mutation, bottlenecks and expansions. The simulation is basically carried out in two steps: In the first step, a historical population is simulated to establish mutation-drift equilibrium and, in the second step, recent population structures are generated, which can be complex.
Version 1.1.0
Project Started 2009
Last Release 8 years, 2 months ago
Citations Sargolzaei M, Schenkel FS, QMSim: a large-scale genome simulator for livestock., Bioinformatics, 03-01-2009 [ Abstract, cited in PMC ]
GSR Certification


Last evaluated02-25-2020 (571 days ago)
Detailed Attributes
Attribute CategoryAttribute
Type of Simulated DataGenotype at Genetic Markers, Diploid DNA Sequence, Haploid DNA Sequence,
VariationsBiallelic Marker, Multiallelic Marker, Single Nucleotide Variation, Microsatellite, Missing Genotypes, Genotype or Sequencing Error,
Simulation MethodForward-time,
Data TypeAllele Frequencies,
File formatProgram Specific,
Data TypeGenotype or Sequence, Phenotypic Trait, Individual Relationship, Demographic, Linkage Disequilibrium, Diversity Measures,
Sequencing Reads
File FormatProgram Specific,
Sample TypeExtended or Complete Pedigrees,
Trait TypeQuantitative,
Evolutionary Features
Population Size ChangesConstant Size, Exponential Growth or Decline, Bottleneck, User Defined,
Gene FlowAdmixed Population, User-defined Matrix,
Life CycleDiscrete Generation Model, Overlapping Generation,
Mating SystemRandom Mating, Monogamous, Polygamous, Assortative or Disassortative,
FecundityConstant Number, Randomly Distributed,
Natural Selection
DeterminantPhenotypic Trait,
ModelsDirectional Selection, Phenotype Threshold,
RecombinationUniform, Varying Recombination Rates,
Mutation ModelsTwo-allele Mutation Model, k-Allele Model, Infinite-allele Model,
Events AllowedPopulation Merge and Split, Varying Demographic Features, Change of Mating Systems,
InterfaceCommand-line, Script-based,
Tested PlatformsWindows, Mac OS X, Linux and Unix,
LanguageC or C++,
LicenseGNU Public License,
GSR CertificationDocumentation, Application,

The following 8 publications are selected examples of applications that used QMSim.


Bermann M, Legarra A, Hollifield MK, Masuda Y, Lourenco D, Misztal I, Validation of single-step GBLUP genomic predictions from threshold models using the linear regression method: An application in chicken mortality., J Anim Breed Genet, 01-01-2021 [Abstract]


González-Diéguez D, Tusell L, Bouquet A, Legarra A, Vitezica ZG, Purebred and Crossbred Genomic Evaluation and Mate Allocation Strategies To Exploit Dominance in Pig Crossbreeding Schemes., G3 (Bethesda), 08-05-2020 [Abstract]

Jibrila I, Ten Napel J, Vandenplas J, Veerkamp RF, Calus MPL, Investigating the impact of preselection on subsequent single-step genomic BLUP evaluation of preselected animals., Genet Sel Evol, 07-29-2020 [Abstract]

Manca E, Cesarani A, Gaspa G, Sorbolini S, Macciotta NPP, Dimauro C, Use of the Multivariate Discriminant Analysis for Genome-Wide Association Studies in Cattle., Animals (Basel), 07-29-2020 [Abstract]

Chen SY, Li C, Luo Z, Li X, Gan J, Jia X, Lai SJ, Wang W, Genotyping-free parentage assignment using RAD-seq reads., Ecol Evol, 06-30-2020 [Abstract]

Nwogwugwu CP, Kim Y, Choi H, Lee JH, Lee SH, Assessment of genomic prediction accuracy using different selection and evaluation approaches in a simulated Korean beef cattle population., Asian-Australas J Anim Sci, 12-01-2020 [Abstract]

Esfandyari H, Fè D, Tessema BB, Janss LL, Jensen J, Effects of Different Strategies for Exploiting Genomic Selection in Perennial Ryegrass Breeding Programs., G3 (Bethesda), 10-05-2020 [Abstract]

Wientjes YCJ, Bijma P, Calus MPL, Optimizing genomic reference populations to improve crossbred performance., Genet Sel Evol, 11-06-2020 [Abstract]

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