makeSimDataset {INSPEcT} | R Documentation |
Generate synthetic rates and concentrations
This method generates rates and concentrations where noise is added according to the desired number of
replicates that the user set as an arguments from the INSPEcT_model object that has been created by the
method of the class INSPEcT makeSimModel
. Rates and concentrations can be generated at the
time-points of interest. This method generates an INSPEcT object that can be modeled and the performance of
the modeling can be tested directly aginst the INSPEcT_model object created by makeSimModel
.
makeSimDataset(object, tpts, nRep, seed = NULL) ## S4 method for signature 'INSPEcT_model' makeSimDataset(object, tpts, nRep, seed = NULL)
object |
An object of class INSPEcT_model, usually the output of |
tpts |
A numeric vector of time points where rates and concentrations have to be evaluated |
nRep |
Number of replicates to simulate |
seed |
A numeric to obtain reproducible results |
An object of the class ExpressionSet containing rates and concentrations
## generate a synthtic data-set of 10 genes based on the real data-set data('rpkms', package='INSPEcT') tpts <- c(0, 1/6, 1/3, 1/2, 1, 2, 4, 8, 16) tL <- 1/6 mycerIds <- newINSPEcT(tpts, tL, rpkms$foursu_exons, rpkms$total_exons, rpkms$foursu_introns, rpkms$total_introns, BPPARAM=SerialParam()) simRates <- makeSimModel(mycerIds, 10) simData <- makeSimDataset(simRates, tpts, 1) ## load simulated datasets data('simRates', package='INSPEcT') data('simData3rep', package='INSPEcT') ## measure sensitivity/sensibility of synthesis, degradation and processing ## rates identification dev.new() rocCurve(simRates, simData3rep) ## measure classification with a different threshold for the chi-squared ## test acceptance of models rocCurve(simRates, simData3rep, cTsh=.2)