oligo (version 1.36.1)

fitProbeLevelModel: Tool to fit Probe Level Models.

Description

Fits robust Probe Level linear Models to all the (meta)probesets in an FeatureSet. This is carried out on a (meta)probeset by (meta)probeset basis.

Usage

fitProbeLevelModel(object, background=TRUE, normalize=TRUE, target="core", method="plm", verbose=TRUE, S4=TRUE, ...)

Arguments

object

FeatureSet object.

background

Do background correction?

normalize

Do normalization?

target

character vector describing the summarization target. Valid values are: 'probeset', 'core' (Gene/Exon), 'full' (Exon), 'extended' (Exon).

method

summarization method to be used.

verbose

verbosity flag.

S4

return final value as an S4 object (oligoPLM) if TRUE. If FALSE, final value is returned as a list.

...

subset to be passed down to getProbeInfo for subsetting. See subset for details.

Value

• fitProbeLevelModel returns an oligoPLM object, if S4=TRUE; otherwise, it will return a list.

References

Bolstad, BM (2004) Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. PhD Dissertation. University of California, Berkeley.

See Also

rma, summarizationMethods, subset

Examples

if (require(oligoData)){
  data(nimbleExpressionFS)
  fit <- fitProbeLevelModel(nimbleExpressionFS)
  image(fit)
  NUSE(fit)
  RLE(fit)
}