rocThresholds: Display rate classification performance with thresholds...
In INSPEcT: Modeling RNA synthesis, processing and degradation with RNA-seq data

Description Usage Arguments Value See Also Examples

A method to visualize the performance in the classification of synthesis, degradation and processing rates based on the comparison of the original simulated rates and the one obtained by the function modelRates. For each rate, classification performance is measured in terms of sensitivity and specificity using a ROC curve analysis. False negatives (FN) represent cases where the rate is identified as constant while it was simulated as varying. False positives (FP) represent cases where INSPEcT identified a rate as varying while it was simulated as constant. On the contrary, true positives (TP) and negatives (TN) are cases of correct classification of varying and constant rates, respectively. Consequently, at increasing brown p-values different sensitivity and specificity can be achieved.

rocThresholds(object, object2, xlim = c(1e-05, 1), plot = TRUE)

## S4 method for signature 'INSPEcT_model,INSPEcT'
rocThresholds(object, object2, xlim = c(1e-05, 1), plot = TRUE)

`object`	An object of class INSPEcT_model, with true rates
`object2`	An object of class INSPEcT or INSPEcT_model, with modeled rates
`xlim`	A numeric representing limits for the x-axis (default is c(1-e-5,1))
`plot`	A logical that indicates whether to plot or not. (default=TRUE)

The thresholds that maximize both sensitivity and specificity

makeSimModel, makeSimDataset, rocCurve

if( Sys.info()["sysname"] != "Windows" ) {
  nascentInspObj <- readRDS(system.file(package='INSPEcT', 'nascentInspObj.rds'))
 
  simRates<-makeSimModel(nascentInspObj, 1000, seed=1)
   
  # newTpts<-simRates@params$tpts
  # nascentSim2replicates<-makeSimDataset(object=simRates
  #                                    ,tpts=newTpts
  #                                    ,nRep=3
  #                                    ,NoNascent=FALSE
  #                                    ,seed=1)
  # nascentSim2replicates<-modelRates(nascentSim2replicates[1:100]
  #                                ,seed=1)
  # (not evaluated to save computational time)
 
  data("nascentSim2replicates",package='INSPEcT')
 
  rocThresholds(simRates[1:100],nascentSim2replicates)
}