https://github.com/bioconductor-source/xps

https://github.com/bioconductor-source/xps

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README

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The package handles the pre-processing and normalization of Affymetrix 
GeneChip expression arrays, including Exon arrays. It is an R wrapper
to XPS (eXpression Profiling System), which is based on ROOT, an object-
oriented framework developed at CERN. Thus, the prior installation of
ROOT is a prerequisite for the usage of this package. ROOT can be
downloaded from http://root.cern.ch. 

Copyright (C) 2000-2017 Christian Stratowa, Vienna, Austria

This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program; if not, a copy of the GNU General Public
License is available at http://www.gnu.org/copyleft/gpl.html. You
can also obtain it by writing to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301  USA.


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Please read the INSTALL file how to install ROOT and package 'xps'

The contents of the INSTALL file are:

I.   Install ROOT:
 Ia.  Install ROOT from source
 Ib.  Install ROOT for Mac OS X
 Ic.  Install ROOT for Mac OS X Mavericks and Yosemite
 Id.  Install ROOT for Mac OS Sierra
 Ie.  Install ROOT for Mac OS El Capitan
 If.  Install ROOT for Windows XP, Vista, and Windows 7
 Ig.  Notes on  ROOT
II.  Install package 'xps':
 IIa.  Install 'xps' from source
 IIb.  Install 'xps' as binary
 IIc.  Install 'xps' for Windows XP, Vista, and Windows 7
 IId.  Tested architectures


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Learning how to use package 'xps'

   The best way to learn how to use package 'xps' is to follow the examples
   in the enclosed vignette "An Introduction to the xps Package".

   As next step it is recommeded to follow the step-by-step examples in the
   script "script4xps.R", which is available in the "examples" subdirectory of
   'xps'. Directory xps/raw contains four CEL-files for chip Test3.CDF, which
   are used in most of the examples. However, real world examples in this script
   include a subset of the Affymetrix Exon Array Dataset human Tissues for  
   HG-U133_Plus_2 arrays, HuEx-1_0-st-v2 arrays and HuGene-1_0-st-v1 arrays.
   The corresponding CEL-files must be downloaded from the Affymetrix web site.

   The use of Affymetrix human Tissues dataset is also explained in more detail
   in the example script "script4exon.R".
   
   Note:
   Please note that the new ThermoFisher Scientic Clariom Arrays, such as the
   human HTA 2.0, mouse MTA 1.0, and rat HT arrays are NOT supported.
    

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Comments regarding the tested architectures:

   1. MacBook Pro Intel Core 2 Duo 2GHz with 2 GB RAM running MacOS X 10.6.6
      All examples were tested, including the Affymetrix human mixture
      dataset for HG-U133_Plus_2, HuGene-1_0-st-v1 AND HuEx-1_0-st-v2.r2

   2. PowerBook Titanium PowerPC G4 550MHz with 1 GB RAM running MacOS X 10.4.9
      Most examples were tested, including the Affymetrix human mixture
      dataset for HG-U133_Plus_2 (HuEx-1_0-st-v2.r2 should also run, as
      I have tested them earlier, but they are very slow on G4 550 MHz)

   3. HP Compaq nx6110 Intel Centrino 1.4 GHz with 512 MB RAM with Fedora Core 4
      All examples were tested, including the Affymetrix human mixture
      dataset for HG-U133_Plus_2  but NOT HuEx-1_0-st-v2.r2.

   4. HP Compaq nx6110 Intel Centrino 1.4 GHz with 512 MB RAM with Windows XP
      Most examples were tested, including the Affymetrix human mixture
      dataset for HG-U133_Plus_2,  HuGene-1_0-st-v1 AND HuEx-1_0-st-v2.r2.
      Note: I could indeed run RMA using 6 exon arrays of the Affmetrix dataset
            with only 512 MB of RAM. However, it may not be possible to run MAS5,
            since the MAS5 background correction uses lots of RAM.
            Furthermore, it was not possible to create the scheme for the exon
            arrays with "import.exon.scheme()", since the Affymetrix files are
            too large; you need at least 1GB RAM.


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