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Last data update: 2014.03.03

R: Compares the distribution of several vectors at a time using...

compNorm

R Documentation

Compares the distribution of several vectors at a time using either boxplots or density curves

Description

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.

Usage

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

Arguments

`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.

Details

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

Value

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

Author(s)

Tarca, A.L.

References

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.

Examples

 # 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")

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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
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(nnNorm)
Loading required package: marray
Loading required package: limma
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/nnNorm/compNorm.Rd_%03d_medium.png", width=480, height=480)
> ### Name: compNorm
> ### Title: Compares the distribution of several vectors at a time using
> ###   either boxplots or density curves
> ### Aliases: compNorm
> ### Keywords: univar
> 
> ### ** Examples
> 
>  # Normalize swirl data with two methods
>  data(swirl)
>  swirlNN<-maNormNN(swirl[,1])

Processing array 1 of 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")
MAD  None : 0.359725 
MAD  Loess : 0.2804819 
MAD  NNets : 0.2837382 
>  #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")
MAD  None : 0.359725 
MAD  Loess : 0.2804819 
MAD  NNets : 0.2837382 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>