mvaMicroRna {AgiMicroRna} | R Documentation

## MA plot

### Description

For each array, the M value is computed for every spot as the difference between the spot intensity in the array and the median intensity for that feature over the whole set of arrays. Every kind of feature is identified with different color (microRNA genes, positive controls, etc ...) The input must be an uRNAList object created by the user, in such a way that the uRNAList$meanS field contains the expression matrix that we want to use in log2 scale (see example below) The gProcessedSignal computed by the Agilent Feature Extaction software normally contains negative values, so a small constant has to be added to the signals before log tranformation.

### Usage

    mvaMicroRna(uRNAList, maintitle, verbose=FALSE)

### Arguments

`uRNAList` | A uRNAList object. It uses the expression matrix stored in the uRNAList$meanS slot. Input expression matrix should be in log2 scale
`maintitle` | character to indicate the title of the graph
`verbose` | logical, if `TRUE`it prints details

### Author(s)

Pedro Lopez-Romero

### Examples

    data(dd.micro)
    op=par(mfrow=c(1,1),ask=TRUE)

    MMM=dd.micro$procS  		  ## gProcessedSignal

    min=min(MMM)        		  ## transforming gProcessedSignal to positive values
    for(i in 1:dim(MMM)[2]){    	  ## before log2 transformation
    MMM[,i]=MMM[,i]+(abs(min)+ 5)
    }
            ddaux=dd.micro
            ddaux$meanS=log2(MMM)
    	mvaMicroRna(ddaux,maintitle="ProcessedSignal",verbose=FALSE)
    	rm(ddaux)
    par(op)

[Package AgiMicroRna version 2.36.0 Index]