PAA (version 1.7.1)

normalizeArrays: Normalize microarray data.

Description

Normalizes EListRaw data and returns an EList object containing normalized data in log2 scale.

Usage

normalizeArrays(elist = NULL, method = "quantile", cyclicloess.method = "pairs", 
controls="internal", group1 = NULL, group2 = NULL, output.path=NULL)

Arguments

elist

EListRaw object containing raw data to be normalized (mandatory).

method

string indicating the normalization method ("cyclicloess", "quantile", "vsn" or "rlm") to be used (mandatory).

cyclicloess.method

string indicating which type of cyclicloess normalization ("pairs", "fast", "affy") should be performed (optional).

controls

sring indicating the ProtoArray controls for rlm normalization (optional). Valid options are "internal" (default), "external", "both" or a regular expression defining a specific control or a specific set of controls.

group1

vector of integers (column indices) indicating all group 1 samples (optional).

group2

vector of integers (column indices) indicating all group 2 samples (optional).

output.path

output.path for ProtoArray rlm normalization (optional).

Value

An EList object with the normalized data in log2 scale is returned.

Details

This function is partially a wrapper to limma's function normalizeBetweenArrays() for inter-array normalization featuring optional groupwise normalization when the arguments group1 AND group2 are assigned. For more information on "cyclicloess", "quantile" or "vsn" see the documentation of the limma package. Furthermore, for ProtoArrays robust linear normalization ("rlm", see Sboner A. et al.) is provided.

For rlm normalization (method = "rlm") the additional argument controls needs to be specified in order to select a set of controls used for normalization. Valid options are "internal" (default), "external" and "both" which refer to the following sets of ProtoArray controls:

• internal: The set of all internal controls spotted on the ProtoArray. The human-IgG series and anti-human-IgG series, which respond to serum and secondary antibodies.
• external: The V5-CMK1 series spotted on the ProtoArray which responds to exogenously added anti-V5 antibody (external control).
• both: The combined set of both the internal and the external controls (i.e., the human-IgG and anti-human-IgG series and the V5-CMK1 series).

Moreover, via controls a regular expression can be passed in order to select a more specific group of controls. Please check the column "Name" in your gpr files in order to obtain the complete list of names of all controls spotted on the ProtoArray. In the following some examples of valid regular expressions are given:

• "^HumanIg" Only human IgGs and IgAs are selected (esp., no anti-human Igs).
• "Anti-HumanIgA" Only anti-human-IgAs are selected (esp., no human IgGs and IgAs).
• "(Anti-HumanIg|^V5control|BSA|ERa)" Only anti-human IgGs and anti-human IgAs, the V5-CMK1 series, BSA and ERa are selected.
• "HumanIgG" Only human IgGs and anti-human IgGs are selected.
• "V5control" Only the V5-CMK1 series is selected.

References

The package limma by Gordon Smyth et al. can be downloaded from Bioconductor (http://www.bioconductor.org/).

Smyth, G. K. (2005). Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds.), Springer, New York, pages 397-420.

Sboner A. et al., Robust-linear-model normalization to reduce technical variability in functional protein microarrays. J Proteome Res 2009, 8(12):5451-5464.

Examples

cwd <- system.file(package="PAA")
load(paste(cwd, "/extdata/Alzheimer.RData", sep=""))
elist <- elist[elist$genes$Block < 10,]
normalized.elist <- normalizeArrays(elist=elist, method="quantile")