Calculate3D {Biocomb}

Plot the 3D-ROC curve

Description

This function plots the 3D-ROC curve using the point coordinates, computed by the function CalculateHUM_ROC. Optionally visualizes the optimal threshold point, which gives the maximal accuracy of the classifier(feature) (see CalcROC).

Usage

Calculate3D(sel,Sn,Sp,S3,optSn,optSp,optS3,thresholds,HUM,
name,print.optim=TRUE)

Arguments

sel

a character value, which is the name of the selected feature.

Sn

a numeric vector of the x-coordinates of the ROC curve..

Sp

a numeric vector of the y-coordinates of the ROC curve.

S3

a numeric vector of the z-coordinates of the ROC curve.

optSn

the first coordinate of the optimal threshold

optSp

the second coordinate of the optimal threshold

optS3

the third coordinate of the optimal threshold

thresholds

a numeric vector with threshold values to calculate point coordinates.

HUM

a numeric vector of HUM values, calculated using function.

name

a character vector of class labels.

print.optim

a boolean parameter to plot the optimal threshold point on the graph. The default value is TRUE.

Details

This function's main job is to plot the 3D-ROC curve according to the given point coordinates.

Value

The function doesn't return any value.

Errors

If there exists NA values for specificity or sensitivity values, or HUM values the plotting fails and an error is triggered with message “Values are missing”

References

Li, J. and Fine, J. P. (2008): ROC Analysis with Multiple Tests and Multiple Classes: methodology and its application in microarray studies.Biostatistics. 9 (3): 566-576.
Natalia Novoselova, Cristina Della Beffa, Junxi Wang, Jialiang Li, Frank Pessler, Frank Klawonn. HUM Calculator and HUM package for R: easy-to-use software tools for multicategory receiver operating characteristic analysis» / Bioinformatics. – 2014. – Vol. 30 (11): 1635-1636 doi:10.1093/ bioinformatics/btu086.

See Also

CalculateHUM_seq, CalculateHUM_ROC

Examples

data(leukemia72)
# Basic example
# class label must be factor
leukemia72[,ncol(leukemia72)]<-as.factor(leukemia72[,ncol(leukemia72)])

xdata=leukemia72

indexF=names(xdata)[10]

indexClass=ncol(xdata)
label=levels(xdata[,indexClass])
indexLabel=label

out=CalculateHUM_seq(xdata,indexF,indexClass,indexLabel)
HUM<-out$HUM
seq<-out$seq
out=CalculateHUM_ROC(xdata,indexF,indexClass,indexLabel,seq)
Calculate3D(indexF,out$Sn,out$Sp,out$S3,out$optSn,out$optSp,out$optS3,
out$thresholds,HUM,indexLabel[seq])