Hello,

I work on Affymetrix Human Exon 1.0 ST.

I trie different methods to analyze this type of microarrays. For the 
moment, I tried APT and Oligo package:
  - I did a RMA in APT with this code:
apt-probeset-summarize -a rma -p HuEx-1_0-st-v2.r2.pgf -c 
HuEx-1_0-st-v2.r2.clf -s HuEx-1_0-st-v2.r2.dt1.hg18.core.ps 
-qc-probesets HuEx-1_0-st-v2.r2.qcc -o OUT_EXON_CORE *.CEL
  - I did a RMA in Oligo package with this code:
library("oligo")
library("pd.huex.1.0.st.v2")
celFiles <- c("Data GSE24976/GSM613529.CEL",
               "Data GSE24976/GSM613530.CEL",
               "Data GSE24976/GSM613531.CEL",
               "Data GSE24976/GSM613532.CEL",
               "Data GSE24976/GSM613533.CEL",
               "Data GSE24976/GSM613534.CEL",
               "Data GSE24976/GSM613535.CEL",
               "Data GSE24976/GSM613536.CEL")
core_rma = rma(data_base, target = "core")
data_base_rma = exprs(core_rma)

When I compare the difference of probesets between the normalized file 
with Oligo package and the normalized file with APT, there is a big 
difference:
- At CORE level:
   * APT: 287 329 probesets
   * Oligo package: 22 011 probesets
- At FULL level:
   * APT: 1 384 231 probesets
   * Oligo package: 266 405 probesets
- At EXTENDED level:
   * APT: 807 038 probesets
   * Oligo package: 133 672 probesets

Why this difference? This difference of probesets between these two 
methods could be explained by an incomplete information in 
pd.huex.1.0.st.v2 package?

Oligo package is really recommanded to analyse Affymetrix Exon Array? 
Which package can I use in order to analyze Affymetrix Exon Array at 
CORE/FULL/EXTENDED level?

Thank you for advance for your answer and your help.


------------------------------

My Session Info:

R version 2.15.1 (2012-06-22)
Platform: x86_64-redhat-linux-gnu (64-bit)

locale:
  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               
LC_TIME=en_US.UTF-8
  [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    
LC_MESSAGES=en_US.UTF-8
  [7] LC_PAPER=C                 LC_NAME=C                  LC_ADDRESS=C
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 
LC_IDENTIFICATION=C

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  
methods   base

other attached packages:
  [1] pd.huex.1.0.st.v2_3.8.0 RSQLite_0.11.2          DBI_0.2-5
  [4] oligo_1.22.0            oligoClasses_1.20.0     affy_1.36.0
  [7] gplots_2.11.0           MASS_7.3-18             KernSmooth_2.23-7
[10] caTools_1.13            bitops_1.0-4.1          gdata_2.12.0
[13] gtools_2.7.0            geneplotter_1.36.0      lattice_0.20-6
[16] annotate_1.36.0         AnnotationDbi_1.20.2    Biobase_2.18.0
[19] BiocGenerics_0.4.0      limma_3.14.1

loaded via a namespace (and not attached):
  [1] affxparser_1.30.0     affyio_1.26.0         BiocInstaller_1.8.3
  [4] Biostrings_2.26.2     bit_1.1-9             codetools_0.2-8
  [7] ff_2.2-9              foreach_1.4.0         GenomicRanges_1.10.2
[10] IRanges_1.16.3        iterators_1.0.6       parallel_2.15.1
[13] preprocessCore_1.20.0 RColorBrewer_1.0-5    splines_2.15.1
[16] stats4_2.15.1         tools_2.15.1          XML_3.95-0.1
[19] xtable_1.7-0          zlibbioc_1.4.0

-- 

Sophie LAMARRE

Statistician - FRANCE


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