INSPEcT (version 1.2.2)

makeSimDataset: Generate synthetic rates and concentrations

Description

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.

Usage

makeSimDataset(object, tpts, nRep, seed = NULL)
"makeSimDataset"(object, tpts, nRep, seed = NULL)

Arguments

object

An object of class INSPEcT_model, usually the output of makeSimModel

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

Value

An object of the class ExpressionSet containing rates and concentrations

See Also

makeSimModel

Examples

## 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)