This package implements classes for files and sets of files for various Affymetrix file formats, e.g. AffymetrixCdfFile, AffymetrixCelFile, and AffymetrixCelSet.  These are designed to be memory efficient but still being fast.  The idea is to keep all data on file and only read data into memory when needed.  Clever caching mechanisms are used to minimize the overhead of data IO.  All of the above is hidden in the package API and for the developer (and the end user), the data is queried as if it lives in memory.  With this design it is only the disk space that limits the number of arrays that can be analyzed.
Henrik Bengtsson [aut, cre, cph],
James Bullard [ctb],
Kasper Hansen [ctb],
Pierre Neuvial [ctb],
Elizabeth Purdom [ctb],
Mark Robinson [ctb],
Ken Simpson [ctb]

Infrastructure, ProprietaryPlatforms, ExonArray, Microarray,
OneChannel, GUI, DataImport, DataRepresentation, Preprocessing,
QualityControl, Visualization, ReportWriting, aCGH,
CopyNumberVariants, DifferentialExpression, GeneExpression,
SNP, Transcription

Recommended: preprocessCore, affyPLM, aroma.light,
affxparser
Analysis of Large Affymetrix Microarray Data Sets

BioC (>= 3.0), Recommended: preprocessCore, affyPLM,
aroma.light, affxparser, DNAcopy
A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samples regardless of computer system.  The only parameter that limits the number of chips that can be processed is the amount of available disk space.  The Aroma Framework has successfully been used in studies to process tens of thousands of arrays.  This package has actively been used since 2006.

Henrik Bengtsson <hb@stat.berkeley.edu>, Pierre Neuvial <pierre@stat.berkeley.edu>, Elizabeth Purdom <epurdom@stat.berkeley.edu>, Mark Robinson <mrobinson@wehi.edu.au>, Ken Simpson <ksimpson@wehi.edu.au>
MASS, methods, splines, matrixStats (>= 0.3.0)

Henrik Bengtsson, James Bullard, Kasper Hansen, Pierre Neuvial,
Elizabeth Purdom, Mark Robinson, Ken Simpson
MASS, methods, splines, matrixStats (>= 0.4.3)