Display rate classification performance

Description

Display rate classification performance

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, sensitivity and specificity are computed using increasing thresholds for the brown p-values, and the ability of correctly classifying a rate is measured through the area under the curve (AUC) for each rate.

Usage

rocCurve(object, object2, cTsh = NULL, plot = TRUE)

## S4 method for signature 'INSPEcT_model,INSPEcT_model'
rocCurve(object, object2, cTsh = NULL,
  plot = TRUE)

## S4 method for signature 'INSPEcT_model,INSPEcT'
rocCurve(object, object2, cTsh = NULL,
  plot = TRUE)

Arguments

Value

A list of objects of class pROC with summary of each roc curve

See Also

makeSimModel, makeSimDataset, rocThresholds

Examples

data('simRates', package='INSPEcT')
data('simData3rep', package='INSPEcT')
rocCurve(simRates, simData3rep)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(INSPEcT)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: BiocParallel
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/INSPEcT/rocCurve.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rocCurve
> ### Title: Display rate classification performance
> ### Aliases: rocCurve rocCurve,INSPEcT_model,INSPEcT-method
> ###   rocCurve,INSPEcT_model,INSPEcT_model-method
> 
> ### ** Examples
> 
> data('simRates', package='INSPEcT')
> data('simData3rep', package='INSPEcT')
> rocCurve(simRates, simData3rep)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>