pspline: Function for two-colour microarray data normalization using...

In TurboNorm: A fast scatterplot smoother suitable for microarray normalization

Description

Wrapper function for two colour microarray data normalization using the P-spline smoother suitable for a RGList- or MarrayRaw-objects.

Usage

pspline(object, background = c("none", "substract"), weights = NULL, nintervals = 100, subset=NULL, showArrays = 0, verbose=FALSE, line.col=2,  line.lty=1, line.lwd=2, ...)

Arguments

object	either a RGList or an MarrayRaw-object.
background	for background substraction use 'substract'. Default is no backgroud substraction.
weights	vector of weights that will be used a for a weighted normalization. The default NULL assumse equal weight 1 for all data points.
nintervals	number of bins in which the data will be divided. The default is 100 bins.
showArrays	either a integer( > 0) or a vector of integers indicating the arrays for which a MA-plot will be produced.
subset	subset of the data on which the normalization will be based. A special case of weighted normalization.
verbose	if TRUE gives additional information on the fit

.

line.col, line.lty, line.lwd	line colour, type and width that will be used in the plots, defaults are col=2, lty=1 and lwd=2.
...	additional graphical arguments for plotting.

Details

if necessary?

Value

The value that will be returned is either a MAList or MarrayNorm-object dependening on the input type.

Author(s)

Chantal van Leeuwen and Maarten van Iterson

References

van Iterson M, Duijkers FA, Meijerink JP, Admiraal P, van Ommen GJ, Boer JM, van Noesel MM, Menezes RX (2012). A novel and fast normalization method for high-density arrays. SAGMB, 11(4).

Paul .H.C. Eilers and Brain D. Marx (1996). Flexible smoothing with B-splines and Penalties. Statistical Science, Vol 11, No. 2, 89-121.

See Also

normalizeWithinArrays, maNormMain

Examples

library(marray)
data(swirl)

x <- pspline(swirl, showArrays=2, pch=20, col="grey")
x <- pspline(swirl, showArrays=2:4, line.col="green")

TurboNorm documentation built on Nov. 8, 2020, 6:46 p.m.