fitWithin {stepNorm}R Documentation

Simple location normalization function for cDNA microarray data


This function performs location normalization on cDNA micoroarray. It operates on class marrayRaw or class marrayNorm. It allows the user to choose from a set of three basic normalization procedures.


fitWithin( = "maA", = "maM", = TRUE, subset=TRUE, fun = "medfit", ...)

Arguments Name of accessor method for spot intensity, usually maA. Name of accessor method for spot statistics, usually the log-ratio maM. Name of accessor method for spot statistic used to stratify the data, usually a layout parameter, e.g. maPrintTip or maCompPlate. If z is not a character, e.g. NULL, the data are not stratified.
subset A "logical" or "numeric" vector indicating the subset of points used to compute the normalization values.
fun Character string specifying the normalization procedure:
for global median location normalization
for global intensity or A-dependent location normalization using the rlm function
for global intensity or A-dependent location normalization using the loess function
... Miscs arguments to be passed in fun


Normalization is typically performed on the expression ratios of cDNA microarray data, using the function specified by argument fun. Currently, this function is to be chosen from: medfit (median), rlmfit (rlm) and loessfit(loess). When is provided as a character string, for example, maPrintTip, the normalization procedure is operated within each print-tip of the slide.


The function fitWithin returns a function(F) with bindings for,,, subset and fun. When the function F is evaluated with an object of class marrayNorm or marrayRaw, it carries out normalization and returns an object of class marrayFit that contains the normalization information as a list with the following list components:

varfun : A character vector of names of predictor variables.
x : A numeric matrix of predictor variables.
y : A numeric matrix of repsonses.
residuals : A numeric matrix of normalized values (typically log ratios (M)).
fitted : A numeric matrix of the fitted values.
enp : The equivalent number of parameters; see loess.
df.residual : The residual degrees of freedom.
fun : A character string indicating the name of the function used for normalization.

Note that the residuals component stores the normalized ratios.


Yuanyuan Xiao,,
Jean Yee Hwa Yang,


Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed (2001). Normalization for cDNA microarray data. In M. L. Bittner, Y. Chen, A. N. Dorsel, and E. R. Dougherty (eds), Microarrays: Optical Technologies and Informatics, Vol. 4266 of Proceedings of SPIE.

See Also



## using the swirl data as example

## median normalization
med <- fitWithin(fun="medfit") <- med(swirl[,1])
norm.M <-$residuals ## matrix of normalized ratios

## rlm normalization
rlmF <- fitWithin(fun="rlmfit")
swirl1.rlm <- rlmF(swirl[,1])

## loess normalization, default span=0.4
loessF <- fitWithin(fun="loessfit")
swirl1.loess <- loessF(swirl[,1])
## loess normalization, span=0.2
loessF.1 <- fitWithin(fun="loessfit", span=0.2)
swirl1.loess.1 <- loessF.1(swirl[,1])

## within-printtip loess normalization
loessP <- fitWithin("maPrintTip", fun="loessfit")
swirl1.loessP <- loessP(swirl[,1])

[Package stepNorm version 1.0.2 Index]