withinNorm {stepNorm}R Documentation

Within-slide normalization function for cDNA spotted microarrays

Description

This function is a wrapper function around fitWtihin and fit2DWithin. It allows the user to choose from a set of thirteen basic location normalization procedures. The function operates on an object of class marrayRaw or marrayNorm and returns an object of class Norm.

Usage

withinNorm(marraySet,  y = "maM", subset = TRUE, norm = c("none", 
    "median", "rlm", "loess", "medianPrintTip", "rlmPrintTip", 
    "loessPrintTip", "medianPlate", "rlmPlate", "loessPlate", 
    "aov2D", "rlm2D", "loess2D", "spatialMedian"), ...)

Arguments

marraySet Object of class marrayRaw or class marrayNorm, containing intensity data for the batch of arrays to be normalized.
y Name of accessor method for spot statistics, usually the log-ratio maM.
subset A "logical" or "numeric" vector indicating the subset of points used to compute the normalization values.
norm A character string specifying the normalization procedures:
none:
no normalization
median:
global median location normalization
rlm:
global intensity or A-dependent robust linear normalization using the rlm function
loess:
global intensity or A-dependent robust nonlinear normalization using the loess function
medianPrintTip:
within-print-tip-group median normalization
rlmPrintTip:
within-print-tip-group intensity or A-dependent robust linear normalization using the rlm function
loessPrintTip:
within-print-tip-group intensity or A-dependent robust nonlinear normalization using the loess function
medianPlate:
within-well-plate-group median normalization
rlmPlate:
within-well-plate-group intensity or A-dependent robust linear normalization using the rlm function
loessPlate:
within-well-plate-group intensity or A-dependent robust nonlinear normalization using the loess function
aov2D:
spatial bivariate location normalization using ANOVA
rlm2D:
spatial bivariate location normalization using the rlm function
loess2D:
spatial bivariate location normalization using the loess function
spatialMedian:
spatial location normalization using a spatial median approach (see Wilson et al. (2003) in reference)
... Misc arguements for the specified norm function

Details

The function withinNorm dispatches to the function fitWithin or fit2DWithin with specified arguments according to the choice of norm. For instance, when norm="loess" for global intenstiy dependent robust nonlinear normalization, withinNorm calls fitWithin(fun="loess") with the default span parameter set at 0.4. If a different span is preferred, it should be input by span=0.2 through the argument ... in the withinNorm function (see example below). For more details see fitWithin, fit2DWithin and individual fitting functions such as loessfit.

Value

An object of class marrayNorm, containing the normalized intensity data.

Author(s)

Yuanyuan Xiao, yxiao@itsa.ucsf.edu,
Jean Yee Hwa Yang, jean@biostat.ucsf.edu

References

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.

D. L. Wilson, M. J. Buckley, C. A. Helliwell and I. W. Wilson (2003). New normalization methods for cDNA microarray data. Bioinformatics, Vol. 19, pp. 1325-1332.

See Also

seqWithinNorm, stepWithinNorm, fitWithin, fit2DWithin, loessfit, rlmfit.

Examples

# Examples use swirl dataset, for description type ? swirl
data(swirl)

# Apply loess normalization for the first slide, span=0.4
## Not run: 
res.swirl1 <- withinNorm(swirl[,1], norm="loess")
## End(Not run)

# Apply loess normalization for the first slide, span=0.2
## Not run: 
res.swirl1 <- withinNorm(swirl[,1], norm="loess", span=0.2)
## End(Not run)
[Package stepNorm version 1.8.0 Index]