normalizeWithinSamples: Within-sample normalization for two-color data
In charm: Analysis of DNA methylation data from CHARM microarrays

Description Usage Arguments Details Value Author(s) Examples

Within-sample (between-channel) normalization for two-color DNA methylation microarray data. This function implements the control probe loess procedure described in Aryee et al., 2011 (PMID: 20858772).

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normalizeWithinSamples(dat, copy=TRUE, 
	method = "loess", scale=c(0.99, 0.99), 
	controlProbes = NULL, controlIndex = NULL, approx=TRUE, breaks=1000, verbose=FALSE)

`dat`	a TilingFeatureSet
`copy`	Only relevant when using disk-backed objects. If TRUE a copy will be made leaving the original object (dat) unchanged. The input object will not be preserved if copy=FALSE
`method`	normalization method. "loess" or "none"
`scale`	a numeric vector (x,y). The xth percentile of each sample is scaled to represent y% methylation. The default c(0.99, 0.99) means probes in the 99% percentile represent 99% methylation. Set to NA for no scaling.
`controlProbes`	character string of the label assigned to non-CpG control probes in the annotation file (i.e. the container column of the .ndf file).
`controlIndex`	a vector of non-CpG control probe indices
`approx`	Bin probes by signal intensity when loess normalizing. Much faster when TRUE
`breaks`	Number of bins to use when approx=TRUE
`verbose`	boolean: Verbose output?