Ringo (version 1.36.0)

preprocess: Preprocess Raw ChIP-chip 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", ChIPChannel="R", inputChannel="G", returnMAList=FALSE, idColumn="PROBE_ID", verbose=TRUE, ...)

Arguments

myRG

object of class RGList

method

string; denoting which normalization method to choose, see below for details

ChIPChannel

string; which element of the RGList holds the ChIP result, see details

inputChannel

string; which element of the RGList holds the untreated input sample; see details

returnMAList

logical; should an MAList object be returned? Default is to return an ExpressionSet object.

idColumn

string; indicating which column of the genes data.frame of the RGList holds the identifier for reporters on the microarray. This column, after calling make.names on it, will make up the unique featureNames of the resulting ExpressionSet. If argument returnMAList is TRUE, this argument is ignored.

verbose

logical; progress output to STDOUT?

...

further arguments to be passed on normalizeWithinArrays and normalizeBetweenArrays

Value

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

Details

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

loess

Calls normalizeWithinArrays with method="loess".

vsn

Calls normalizeBetweenArrays with method="vsn".

Gquantile

Calls normalizeBetweenArrays with method="Gquantile".

Rquantile

Calls normalizeBetweenArrays with method="Rquantile".

median

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)

Gvsn

Learns vsn model on green channel intensities only and applies that transformation to both channels before computing fold changes.

Rvsn

Learns vsn model on red channel intensities only and applies that transformation to both channels before computing fold changes.

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".

Mostly with two-color ChIP-chip, the ChIP sample is marked with the red Cy5 dye and for the untreated input sample the green Cy3 dye is used. In that case the RGListmyRG's element R holds the ChIP data, and element G holds the input data. If this is not the case with your data, use the arguments ChIPChannel and inputChannel to specify the respective elements of myRG.

See Also

normalizeWithinArrays, normalizeBetweenArrays, malist, ExpressionSet, vsnMatrix

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"))