Build the synthetic rates shaped on a dataset

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Description

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.

Usage

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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)

Arguments

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

Details

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.

Value

An object of class INSPEcT_model with synthetic rates

See Also

makeSimDataset

Examples

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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)

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