oligo (version 1.36.1)

rma-methods: RMA - Robust Multichip Average algorithm

Description

Robust Multichip Average preprocessing methodology. This strategy allows background subtraction, quantile normalization and summarization (via median-polish).

Usage

## S3 method for class 'ExonFeatureSet':
rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
  ## S3 method for class 'HTAFeatureSet':
rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
  ## S3 method for class 'ExpressionFeatureSet':
rma(object, background=TRUE, normalize=TRUE, subset=NULL)
  ## S3 method for class 'GeneFeatureSet':
rma(object, background=TRUE, normalize=TRUE, subset=NULL, target="core")
  ## S3 method for class 'SnpCnvFeatureSet':
rma(object, background=TRUE, normalize=TRUE, subset=NULL)

Arguments

object

Exon/HTA/Expression/Gene/SnpCnv-FeatureSet object.

background

Logical - perform RMA background correction?

normalize

Logical - perform quantile normalization?

subset

To be implemented.

target

Level of summarization (only for Exon/Gene arrays)

References

Rafael. A. Irizarry, Benjamin M. Bolstad, Francois Collin, Leslie M. Cope, Bridget Hobbs and Terence P. Speed (2003), Summaries of Affymetrix GeneChip probe level data Nucleic Acids Research 31(4):e15

Bolstad, B.M., Irizarry R. A., Astrand M., and Speed, T.P. (2003), A Comparison of Normalization Methods for High Density O ligonucleotide Array Data Based on Bias and Variance. Bioinformatics 19(2):185-193 Irizarry, RA, Hobbs, B, Collin, F, Beazer-Barclay, YD, Antonellis, KJ, Scherf, U, Speed, TP (2003) Exploration, Normalizati on, and Summaries of High Density Oligonucleotide Array Probe Level Data. Biostatistics. Vol. 4, Number 2: 249-264

See Also

snprma

Examples

if (require(maqcExpression4plex) & require(pd.hg18.60mer.expr)){
xysPath <- system.file("extdata", package="maqcExpression4plex")
xysFiles <- list.xysfiles(xysPath, full.name=TRUE)
ngsExpressionFeatureSet <- read.xysfiles(xysFiles)
summarized <- rma(ngsExpressionFeatureSet)
show(summarized)
}