Introduction | Simulating Mixed-Type Clinical Data | Model Subtypes and Survival | Simulate Raw Data | Apply Clinically Realistic Noise | Simulate Mixed-Type Data | The MixedTypeEngine
Package: Umpire 2.0.11
Kevin R. Coombes
Umpire: Simulating Realistic Gene Expression and Clinical Data
The Ultimate Microrray Prediction, Reality and Inference Engine (UMPIRE) is a package to facilitate the simulation of realistic microarray data sets with links to associated outcomes. See Zhang and Coombes (2012) <doi:10.1186/1471-2105-13-S13-S1>. Version 2.0 adds the ability to simulate realistic mixed-typed clinical data.
Authors:
Umpire_2.0.11.tar.gz
Umpire_2.0.11.tar.gz(r-4.7-any)Umpire_2.0.11.tar.gz(r-4.6-any)
Umpire_2.0.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Umpire/json (API)
| # Install 'Umpire' in R: |
| install.packages('Umpire', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/oompa
Last updated from:0adbfa3434. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 179 | ||
| source / vignettes | OK | 209 | ||
| linux-release-x86_64 | OK | 209 | ||
| wasm-release | OK | 168 |
Exports:addControlalterMeanalterSDBlockHyperParametersblurCancerEngineCancerModelClinicalEngineClinicalNoiseModelcorrelcovarEngineEngineWithActivitygetDaisyTypesgetDataTypesIndependentLogNormalIndependentNormalinvGammaMultiplemakeBlockStructuremakeDataTypesMixedTypeEngineMVNncolnComponentsnHitsPerPatternNoiseModelnormalOffsetNormalVsCancerEngineNormalVsCancerModelnPatternsnPossibleHitsnrowoutcomeCoefficientsrandsummarysurvivalCoefficientsSurvivalModel
Dependencies:abindbackportsBimodalIndexbootbroomcarcarDatacliclustercolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmc2dmclustmgcvminqamodelrmvtnormnlmenloptrnnetnumDerivoompaBasepbkrtestpillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo
Umpire 2.0: Clinically Realistic Simulations
Last update: 2020-08-02
Started: 2020-04-14
Umpire 2.0: Simulating Associated Survival
Base Survival | Default method to generate beta coefficients. | Better method to generate beta coefficients. | Fewer possible hits | Appendix
Last update: 2020-06-01
Started: 2020-06-01
Umpire Primer
Introduction | The gene expression model | Additive and Multiplicative Noise | Gene Expression | Appendix
Last update: 2017-07-11
Started: 2017-07-11
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Method "addControl" | addControl addControl,ANY-method addControl,CancerEngine-method addControl,CancerModel-method addControl-method |
| Methods "alterMean" and "alterSD" | alterMean alterMean,ANY-method alterMean-method alterSD alterSD,ANY-method alterSD-method |
| The "BlockHyperParameters" Class | BlockHyperParameters BlockHyperParameters-class makeBlockStructure |
| Method "blur" | blur blur,ANY-method blur-method |
| The "CancerEngine" Class | CancerEngine CancerEngine-class ClinicalEngine nComponents,CancerEngine-method nrow,CancerEngine-method rand,CancerEngine-method summary,CancerEngine-method |
| The "CancerModel" Class | CancerModel CancerModel-class ncol,CancerModel-method nHitsPerPattern nPatterns nPossibleHits nrow,CancerModel-method outcomeCoefficients rand,CancerModel-method summary,CancerModel-method survivalCoefficients |
| A Noise Model for Clinical Data | ClinicalNoiseModel |
| The "Engine" Class | alterMean,Engine-method alterSD,Engine-method Engine Engine-class nComponents,Engine-method nrow,Engine-method rand,Engine-method summary,Engine-method |
| The "EngineWithActivity" Class | EngineWithActivity EngineWithActivity-class rand,EngineWithActivity-method summary,EngineWithActivity-method |
| The "IndependentLogNormal" Class | alterMean,IndependentLogNormal-method alterSD,IndependentLogNormal-method IndependentLogNormal IndependentLogNormal-class nrow,IndependentLogNormal-method rand,IndependentLogNormal-method summary,IndependentLogNormal-method |
| The "IndependentNormal" Class | alterMean,IndependentNormal-method alterSD,IndependentNormal-method IndependentNormal IndependentNormal-class nrow,IndependentNormal-method rand,IndependentNormal-method summary,IndependentNormal-method |
| Discretize a Continuous Data Set to Mixed Types | getDaisyTypes getDataTypes makeDataTypes |
| The "MixedTypeEngine" Class | MixedTypeEngine MixedTypeEngine-class rand,MixedTypeEngine-method summary,MixedTypeEngine-method |
| The "MVN" Class | alterMean,MVN-method alterSD,MVN-method correl covar MVN MVN-class nrow,MVN-method rand,MVN-method summary,MVN-method |
| Method "nComponents" | nComponents nComponents,ANY-method nComponents-method |
| The "NoiseModel" Class | blur,NoiseModel-method NoiseModel NoiseModel-class summary,NoiseModel-method |
| Simulating Cancer Versus Normal Datasets | NormalVsCancerEngine NormalVsCancerModel |
| Method "rand" | rand rand,ANY-method rand-method |
| The "SurvivalModel" Class | rand,SurvivalModel-method SurvivalModel SurvivalModel-class |
| Transform functions | invGammaMultiple normalOffset |