| preprocess {Ringo} | R Documentation |
Calls one of various limma functions to transform raw probe
intensities into (background-corrected) normalized log ratios
(M-values).
preprocess(myRG, method="vsn", ChIPChannel="R", inputChannel="G",
returnMAList=FALSE, idColumn="PROBE_ID", verbose=TRUE, ...)
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 |
The procedure and called limma functions depend on the choice of
method.
normalizeWithinArrays with
method="loess".normalizeBetweenArrays with
method="vsn".normalizeBetweenArrays with
method="Gquantile".normalizeBetweenArrays with
method="Rquantile".normalizeWithinArrays with
method="median".vsn model on green channel intensities
only and applies that transformation to both channels before
computing fold changes.vsn model on red channel intensities
only and applies that transformation to both channels before
computing fold changes.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.
Returns normalized, transformed values as an object of class
ExpressionList or MAList.
Since Ringo version 1.5.6, this function does not call limma's
function backgroundCorrect directly any
longer. If wanted by the user, background correction should be
indicated as additional arguments passed on to
normalizeWithinArrays or
normalizeBetweenArrays, or alternatively call
backgroundCorrect on the RGList before
preprocessing.
Joern Toedling toedling@ebi.ac.uk
normalizeWithinArrays,
normalizeBetweenArrays,
malist,ExpressionSet,
vsnMatrix
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"))