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install ecoliLeucine and preprocess it with RMA.

source("http://bioconductor.org/biocLite.R")
## Bioconductor version 2.14 (BiocInstaller 1.14.2), ?biocLite for
##   help
biocLite(c("affy", "ecoliLeucine"))
## BioC_mirror: http://bioconductor.org
## Using Bioconductor version 2.14 (BiocInstaller 1.14.2), R version
##   3.1.1.
## Installing package(s) 'affy' 'ecoliLeucine'
## package 'affy' successfully unpacked and MD5 sums checked
## package 'ecoliLeucine' successfully unpacked and MD5 sums checked
## 
## The downloaded binary packages are in
##  C:\Users\knishida\AppData\Local\Temp\RtmpeU3Fl5\downloaded_packages
## Warning: installed directory not writable, cannot update packages 'class',
##   'mgcv'
library("affy")
## Loading required package: BiocGenerics
## Loading required package: parallel
## 
## Attaching package: 'BiocGenerics'
## 
## The following objects are masked from 'package:parallel':
## 
##     clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
##     clusterExport, clusterMap, parApply, parCapply, parLapply,
##     parLapplyLB, parRapply, parSapply, parSapplyLB
## 
## The following object is masked from 'package:stats':
## 
##     xtabs
## 
## The following objects are masked from 'package:base':
## 
##     anyDuplicated, append, as.data.frame, as.vector, cbind,
##     colnames, do.call, duplicated, eval, evalq, Filter, Find, get,
##     intersect, is.unsorted, lapply, Map, mapply, match, mget,
##     order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
##     rbind, Reduce, rep.int, rownames, sapply, setdiff, sort,
##     table, tapply, union, unique, unlist
## 
## Loading required package: Biobase
## Welcome to Bioconductor
## 
##     Vignettes contain introductory material; view with
##     'browseVignettes()'. To cite Bioconductor, see
##     'citation("Biobase")', and for packages 'citation("pkgname")'.
library("ecoliLeucine")
## Loading required package: ecolicdf
## Warning: replacing previous import by 'utils::head' when loading 'ecolicdf'
## Warning: replacing previous import by 'utils::tail' when loading 'ecolicdf'
## 
data("ecoliLeucine")
eset = rma(ecoliLeucine)
## Background correcting
## Normalizing
## Calculating Expression

export as csv.

write.exprs(eset, file="ecoliLeucine-eset.csv", sep=",")