doGCRMA: Robust Multichip Analysis (GCRMA)

In HenrikBengtsson/aroma.affymetrix: Analysis of Large Affymetrix Microarray Data Sets

Robust Multichip Analysis (GCRMA)

Description

Robust Multichip Analysis (GCRMA) based on [1]. The algorithm is processed in bounded memory, meaning virtually any number of arrays can be analyzed on also very limited computer systems. The method replicates the results of gcrma (package gcrma) with great precision.

Usage

  ## S3 method for class 'AffymetrixCelSet'
doGCRMA(csR, arrays=NULL, type=c("fullmodel", "affinities"), uniquePlm=FALSE, drop=TRUE,
  verbose=FALSE, ...)
  ## Default S3 method:
doGCRMA(dataSet, ..., verbose=FALSE)

Arguments

csR, dataSet	An AffymetrixCelSet (or the name of an AffymetrixCelSet).
arrays	A integer vector specifying the subset of arrays to process. If NULL, all arrays are considered.
type	A character string specifying what type of model to use for the GCRMA background correction. For more details, see GcRmaBackgroundCorrection.
uniquePlm	If TRUE, the log-additive probe-summarization model is done on probeset with unique sets of probes. If FALSE, the summarization is done on "as-is" probesets as specified by the CDF.
drop	If TRUE, the summaries are returned, otherwise a named list of all intermediate and final results.
verbose	See Verbose.
...	Additional arguments used to set up AffymetrixCelSet (when argument dataSet is specified).

Value

Returns a named list, iff drop == FALSE, otherwise only ChipEffectSet object.

Author(s)

Henrik Bengtsson

References

[1] Z. Wu, R. Irizarry, R. Gentleman, F.M. Murillo & F. Spencer. A Model Based Background Adjustment for Oligonucleotide Expression Arrays, JASA, 2004.

HenrikBengtsson/aroma.affymetrix documentation built on Feb. 20, 2024, 9:07 p.m.