makeSimModel {INSPEcT} | R Documentation |
Build the synthetic rates shaped on a dataset
This method allow the creation of synthesis, degradation and processing rates for a certain number of genes.
The rates are created according to the distributions of the real data-set which is given as an input of the
method. Different proportions of constant varying rates can be set and a new vector of time points can be
provided. This method has to be used before the makeSimDataset
method.
makeSimModel(object, nGenes, newTpts = NULL, probs = c(constant = 0.5, sigmoid = 0.3, impulse = 0.2), na.rm = TRUE, seed = NULL) ## S4 method for signature 'INSPEcT' makeSimModel(object, nGenes, newTpts = NULL, probs = c(constant = 0.5, sigmoid = 0.3, impulse = 0.2), na.rm = TRUE, seed = NULL)
object |
An object of class INSPEcT |
nGenes |
A numeric with the number of synthtic genes to be created |
newTpts |
A numeric verctor with time points of the synthtic dataset, if NULL the time points of the real dataset will be used |
probs |
A numeric vector wich describes the probability of a rate to be constant, shaped like a sigmoid or like an impulse model |
na.rm |
A logical that set whether missing values in the real dataset should be removed |
seed |
A numeric to obtain reproducible results |
The method makeSimModel
generates an object of class INSPEcT_model that stores the parametric functions to genrate clean rates of a time-course. To any of the rates also a noise variance is associate but not used yet. In a typical workflow the output of makeSimModel
is the input of the method makeSimDataset
, that build the noisy rates and concentrations, given a specified number of replicates.
An object of class INSPEcT_model with synthetic rates
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()) ## generate a synthtic data-set of 10 genes based on the real data-set simRates <- makeSimModel(mycerIds, 10) simData <- makeSimDataset(simRates, tpts, 1) ## measure sensitivity/sensibility of synthesis, degradation and processing ## rates identification data('simRates', package='INSPEcT') data('simData3rep', package='INSPEcT') rocCurve(simRates, simData3rep) ## measure classification with a different threshold for the chi-suared ## test acceptance of models rocCurve(simRates, simData3rep, cTsh=.2) ## generate a synthtic data-set of 10 genes based on the real data-set ## with more replicates and more time points ## Not run: newTpts <- c(0, 1/6, 1/3, 1/2, 1, 1.5, 2, 4, 8, 12, 16, 24) simRates <- makeSimModel(mycerIds, 10, newTpts=newTpts) simData <- makeSimDataset(simRates, newTpts, 3) ## End(Not run)