preprocess {Ringo}R Documentation

Preprocess Nimblegen Raw Intensities

Description

Calls one of various limma functions to transform raw probe intensities into (background-corrected) normalized log ratios (M-values).

Usage

preprocess(myRG, method = "vsn", returnMAList=FALSE, verbose=TRUE, ...)

Arguments

myRG object of class RGList
method string; denoting which normalization method to choose
returnMAList logical; should an MAList object be returned? Default is to return an ExpressionSet object.
verbose logical; progress output to STDOUT?
... further arguments to be passed on normalizeWithinArrays and normalizeBetweenArrays

Details

The procedure and called limma functions depend on the choice of method.

loess
First performs background correction of intensity values using limma's function backgroundCorrect with method="normexp" and offset=50. Then calls normalizeWithinArrays.
vsn
Does not do any background correction, but rather directly calls normalizeBetweenArrays with method="vsn".
Gquantile
Does not do any background correction, but rather directly calls normalizeBetweenArrays with method="Gquantile".
median
First performs background correction of intensity values using limma's function backgroundCorrect with method="normexp" and offset=50. Then calls normalizeWithinArrays with method="median".
nimblegen
Scaling procedure used by Nimblegen. Yields scaled log-ratios by a two step procedure: srat = log2(R) - log2(G) srat = srat - tukey.biweight(srat)
none
No normalization of probe intensities, takes raw log2(R)-log2(G) as component M and (log2(R)+log2(G))/2 as component A; uses normalizeWithinArrays with method="none".

Value

Returns normalized, transformed values as an object of class ExpressionList or MAList.

Author(s)

Joern Toedling toedling@ebi.ac.uk

See Also

backgroundCorrect, normalizeWithinArrays, normalizeBetweenArrays, malist,ExpressionSet, tukey.biweight

Examples

   exDir <- system.file("exData",package="Ringo")
   exRG <- readNimblegen("example_targets.txt","spottypes.txt",path=exDir)
   exampleX <- preprocess(exRG)
   sampleNames(exampleX) <- 
     make.names(paste(exRG$targets$Cy5,"vs",exRG$targets$Cy3,sep="_"))
   print(exampleX)

   ### compare VSN to NimbleGen's tukey-biweight scaling
   exampleX.NG <- preprocess(exRG, method="nimblegen")
   sampleNames(exampleX.NG) <- sampleNames(exampleX)
   if (interactive())
     corPlot(cbind(exprs(exampleX),exprs(exampleX.NG)),
       grouping=c("VSN normalized","Tukey-biweight scaled"))

[Package Ringo version 1.2.0 Index]