depthTools (version 0.7)

scalecurve: Computation and Representation of the Scale Curve

Description

scalecurve computes the scale curve of a given group, based on the modified band depth, at a given value p as the area of the band delimited by the [np] most central observations, where [np] is the largest integer smaller than np.

Usage

scalecurve(x,y=NULL,xlab="p",ylab="A(p)",main="Scale curve",lwd=2,
           ...)

Arguments

x

a data matrix containing the observations (samples) by rows and the variables (genes) by columns

y

an optional vector (numeric or factor) of length equal to the number of rows in x, containing the class of each observation. If unprovided, then all the elements in x are assumed to belong to a single class

xlab

label in the x axis

ylab

label in the y axis

main

plot title

lwd

line widths for the corresponding scale curve(s)

...

graphical parameters to be passed to 'plot'

Value

r

the value of the scale curve at equidistant values of p, determined by the number of observation within each class. If y is not provided, then r is a vector, otherwise is a list with as many components as classes described by y.

Details

The scale curve measures the increase in the area of the band determined by the fraction p most central curves, where p moves from 0 to 1, thus providing a measure of the sample dispersion. If the data set is represented in parallel coordinates, then the area is computed using the trapezoid formula.

References

Lopez-Pintado, S. et al. (2010). Robust depth-based tools for the analysis of gene expression data. Biostatistics, 11 (2), 254-264.

Examples

# NOT RUN {
## scale curve of a single data set
  ## simulated data
  set.seed(0)  
  x <- matrix(rnorm(100),10,10)
  scalecurve(x)

  ## real data
  data(prostate)
  prost.x<-prostate[,1:100]
  prost.y<-prostate[,101]
  scalecurve(prost.x[prost.y==0,])  ## scale curve of normal samples
  scalecurve(prost.x[prost.y==1,])  ## scale curve of tumoral samples
  
## scalecurve of different groups 
  ## simulated data
  x <- matrix(rnorm(100),10,10)
  y <- c(rep("tumoral",5),rep("normal",5))
  scalecurve(x,y)

  ## real data
  labels<-prost.y 
  labels[prost.y==0]<-"normal"; labels[prost.y==1]<-"tumoral"
  scalecurve(prost.x,labels)  
# }