GSR: Simulator - OncoSimulR

Basic Package Attributes
AttributeValue
Title OncoSimulR
Short Description BioConductor package for Forward Genetic Simulation of Cancer Progresion with Epistasis
Long Description An R/BioConductor package that provides functions for forward population genetic simulation in asexual populations, with special focus on cancer progression. Fitness can be an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, order restrictions in mutation accumulation, and order effects. Mutation rates can differ between genes, and we can include mutator/antimutator genes (to model mutator phenotypes). Simulations use continuous-time models and can include driver and passenger genes and modules. Also included are functions for simulating random DAGs of the type found in Oncogenetic Trees, Conjunctive Bayesian Networks, and other cancer progression models; plotting and sampling from single or multiple realizations of the simulations, including single-cell sampling; plotting the parent-child relationships of the clones; generating random fitness landscapes (Rough Mount Fuji, House of Cards, and additive models) and plotting them.
Keywords cancer, mutation, simulation, evolution, mutator, epistasis, fitness landscape, cancer progression models
Version 2.13.1
Project Started 2015
Last Release 1 year, 8 months ago
Homepagehttps://github.com/rdiaz02/OncoSimul
Citations Diaz-Uriarte R, OncoSimulR: genetic simulation with arbitrary epistasis and mutator genes in asexual populations., Bioinformatics, 06-15-2017 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluated01-10-2019 (646 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 DataHaploid DNA Sequence,
VariationsBiallelic Marker, Genotype or Sequencing Error,
Simulation MethodForward-time,
Input
Data TypeAncestral Sequence, Other,
File formatProgram Specific,
Output
Data TypeGenotype or Sequence, Individual Relationship, Demographic, Mutation, Diversity Measures, Fitness,
Sequencing Reads
File FormatProgram Specific,
Sample TypeRandom or Independent, Longitudinal, Other,
Phenotype
Trait Type
Determinants
Evolutionary Features
Demographic
Population Size ChangesExponential Growth or Decline, Logistic Growth,
Gene Flow
Spatiality
Life CycleOverlapping Generation,
Mating System
FecundityIndividually Determined, Influenced by Environment,
Natural Selection
DeterminantSingle-locus, Multi-locus, Fitness of Offspring, Environmental Factors,
ModelsDirectional Selection, Multi-locus models, Epistasis, Random Fitness Effects,
Recombination
Mutation ModelsTwo-allele Mutation Model,
Events AllowedVarying Genetic Features,
Other
InterfaceCommand-line, Script-based,
Development
Tested PlatformsWindows, Mac OS X, Linux and Unix,
LanguageC or C++, R,
LicenseGNU Public License,
GSR CertificationAccessibility, Documentation, Application, Support,

The following 3 publications are selected examples of applications that used OncoSimulR.

2018

Diaz-Uriarte R, Cancer progression models and fitness landscapes: a many-to-many relationship., Bioinformatics, 03-01-2018 [Abstract]

Schoen D, Schultz S, Somatic mutation and evolution in plants, Annual Review of Ecology, Evolution, and Systematics, vol. 50, in press, None

Diaz-Uriarte R, Vasallo C, Every which way? On predicting tumor evolution using cancer progression models, bioRxiv, None [Abstract]


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