quantileNormalize {HELP} | R Documentation |
Apply quantile normalization to multiple bins of data, divided by a sliding window approach
quantileNormalize(x, y, ...)
x |
the vector of numerical data to be normalized. If x is a matrix it is interpreted as a vector. x can also be of class "ExpressionSet" . |
y |
an additional vector of numerical data to be used for binning. If y is a matrix it is interpreted as a vector. y can also be of class "ExpressionSet" . |
... |
Arguments to be passed to methods (see quantileNormalize-methods ):
element AssayData to use for a given ExpressionSet input (default is "exprs") sample sampleNames to use as data (default is 1). Can be a character matching a sample name or simply an integer indicating which sample to choose. See getSamples . feature featureData to use as binning variable (default is 1). Can be a character matching varLabel or simply an integer indicating which feature to choose. See getFeatures . num.bins num.steps mode type quantile . na.rm ... quantile . See quantile . |
Returns a vector of normalized numerical data according to input parameters.
Reid F. Thompson (rthompso@aecom.yu.edu)
quantileNormalize-methods
, quantile
#demo(pipeline,package="HELP") x <- rep(1:100,10)+10*rep(1:10,each=100) y <- rep(1:20,each=50) d <- density(quantileNormalize(x,y,num.bins=20,num.steps=1,mode="discrete")) plot(density(x)) lines(d$x,d$y/3,col="red") #rm(x,y,d)