[BioC] Missing probesets when creating Affymetrix GeneChip miRNA 4.0 CDF package using makecdfenv package

[Lei Huang [guest]]

Dear all,

I am working on a set of Affymetrix GeneChip miRNA 4.0 microarray data and would like to perform differential expression analysis using Bioconductor packages. Since this is a fairly new platform, no CDF and annotation packages are available in bioconductor repository at the moment. Affymetrix folks kindly provided me miRNA 4.0 CDF file as well as sample CEL data. So I desided to create a CDF package by my own using make.cdf.package() from makecdfenv package. I was able to make the package and install it without trouble. However, after I read the raw CEL files and normalized the affybatch with vsnrma()/rma(), I found the number of probesets is only 25065 while the number is 36249 in original Affymetrix miRNA 4.0 CDF file. I am aware that from version 4, Affymetrix changed their naming convention for the probeset IDs, but this shouldn't cause the problem of missing probesets. What I did wrong? I would really appreciate if anyone could give me some hints/advices on solving this 
 problem. 

-Lei

--
Lei Huang
Center for Research Informatics
Biological Science Division
University of Chicago
http://cri.uchicago.edu
--

P.S. The following are the code and output from my R session:

> setwd("~/Documents/Project/mirna/GeneChip 4-0 Array Sample Data")
> library(affy)
> library(makecdfenv)
Loading required package: affyio
> pkgpath <- tempdir()
> pname <- cleancdfname(whatcdf("20131118_Human-Brain-AM7962-130ng_rep1_(miRNA-4_0).CEL"))
> make.cdf.package("miRNA-4_0-st-v1.cdf", cdf.path="~/Documents/Project/mirna/miRNA-4_0-st-v1_CDF", 
+                  compress=FALSE, species = "", packagename=pname, package.path = pkgpath)
Reading CDF file.
Creating CDF environment
Wait for about 251 dots.............................................................................................................................................................................................................................................................
Creating package in /var/folders/rh/rrlg3bcs6kgcj89zm4mgjjxh0000gq/T//RtmpRos3Be/mirna40cdf 

README PLEASE:
A source package has now been produced in
/var/folders/rh/rrlg3bcs6kgcj89zm4mgjjxh0000gq/T//RtmpRos3Be/mirna40cdf.
Before using this package it must be installed via 'R CMD INSTALL'
at a terminal prompt (or DOS command shell).
If you are using Windows, you will need to get set up to install packages.
See the 'R Installation and Administration' manual, specifically
Section 6 'Add-on Packages' as well as 'Appendix E: The Windows Toolset'
for more information.

Alternatively, you could use make.cdf.env(), which will not require you to install a package.
However, this environment will only persist for the current R session
unless you save() it.

## install the cdf package from shell
## cd to mirna40cdf location
## R CMD INSTALL mirna40cdf

> library(limma)
> library(vsn)
> library(mirna40cdf)
>
> affybatch <- ReadAffy(filenames=list.files())
> affybatch at cdfName
[1] "miRNA-4_0"

## normalization
> eset.norm <- vsnrma(affybatch)
vsn2: 292681 x 8 matrix (1 stratum). 
Please use 'meanSdPlot' to verify the fit.
Calculating Expression

## only 25,065 probesets, the original Affymetrix cdf file contains 36,249 probesets
> dim(eset.norm)
Features  Samples 
   25065        8 


 -- output of sessionInfo(): 

> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] mirna40cdf_1.38.0    AnnotationDbi_1.24.0 vsn_3.30.0          
[4] limma_3.18.9         makecdfenv_1.38.0    affyio_1.30.0       
[7] affy_1.40.0          Biobase_2.22.0       BiocGenerics_0.8.0  

loaded via a namespace (and not attached):
 [1] BiocInstaller_1.12.0  compiler_3.0.2        DBI_0.2-7            
 [4] grid_3.0.2            IRanges_1.20.6        lattice_0.20-24      
 [7] preprocessCore_1.24.0 RSQLite_0.11.4        stats4_3.0.2         
[10] tools_3.0.2           zlibbioc_1.8.0       


--
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