compNorm: Compares the distribution of several vectors at a time using...
In nnNorm: Spatial and intensity based normalization of cDNA microarray data based on robust neural nets

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/compNorm.R

This function was concieved to easily compare several normalization methods in terms of variability of log-ratios, M. Basically it produces two plots: The first is a the density plot of the several matrices passed as arguments, while the second is a box plot. Median of absolute deviations for each method is printed on screen.

1	compNorm(x,...,bw="AUTO",xlim=c(-3,3),titles="AUTO",type="d")

`x`	A vector of numerical values, e.q. the M values of a data set: `as.vector(maM(swirl))`.
`...`	An undefined number of objects similar with `x`.
`bw`	Band width required to compute the density distribution. `"AUTO"` will adjust `bw` to a suitable value.
`xlim`	The range for abscissa of the density plots.
`titles`	Names to be displayed the charts legend. `"AUTO"` will use the matrices names passed as arguments. .
`type`	If set to `"d"`, density plot will be shown; if set to `"d"` box plot will be shown.

This function is used to compare the normalized log ratios M obtained with several normalization methods.

NULL, this function only displays charts and prints on the screen some statistics.

Tarca, A.L.

A. L. Tarca, J. E. K. Cooke, and J. Mackay. Robust neural networks approach for spatial and intensity dependent normalization of cDNA data. Bioinformatics. 2004,submitted.

maNormNN

 # Normalize swirl data with two methods
 data(swirl)
 swirlNN<-maNormNN(swirl[,1])
 swirlLoess<-maNormMain(swirl[,1]) 
 nms<-c("None","Loess","NNets")
 #compare distributions: density plot
 compNorm(as.vector(maM(swirl[,1])),as.vector(maM(swirlLoess)),as.vector(maM(swirlNN)),xlim=c(- 2,2),bw="AUTO",titles=nms,type="d")
 #compare distributions: box plot
 compNorm(as.vector(maM(swirl[,1])),as.vector(maM(swirlLoess)),as.vector(maM(swirlNN)),xlim=c(- 2,2),bw="AUTO",titles=nms,type="b")