Hi,

 

I am a Ph.D. student from Québec, Canada. I’m a beginner with R and
Bioconductor. Until now the only experience I have is in analyzing
microarray data using affy and limma packages. Now I am trying to analyze
Rat Gene 10 st arrays and I would like to run RMA analysis and Smyth
moderated t test on those arrays. Since no cdf official package is available
for those arrays, after reading many of the questions and responses on this
mailing list, I decided to use pdInfoBuilder, oligo and limma packages to
run analysis. The problem is, at the end, I get expression and differential
expression measured for all probe separately but not the calculated
expression representing all probe of each gene. When I run RMA, I got only
two steps, Background correcting and Normalizing but not Calculating
expression. Do you know how I can get differential expression calculated for
each gene? I don’t know if the problem is in the package I built or if I can
use some code to answer this question. I list all codes used to build and
install the package “pd.ragene.1.0.st.v1” and used to analyze expression
arrays below.

 

Many thanks for your help,

 

Anne-Marie Madore

 

 

 

 

## building the package

 

> library(Biobase)

Loading required package: tools

 

Welcome to Bioconductor

 

  Vignettes contain introductory material. To view, type

  'openVignette()'. To cite Bioconductor, see

  'citation("Biobase")' and for packages 'citation(pkgname)'.

 

> library(pdInfoBuilder)

Loading required package: RSQLite

Loading required package: DBI

Loading required package: affxparser

Loading required package: oligo

Loading required package: splines

Loading required package: preprocessCore

Loading required package: AnnotationDbi

Loading required package: oligoClasses

oligo Package - Series 1.5.x

> setwd("D:/Anne-Marie/Doctorat/puces ADN macrophages/puces rat/Annie
Dube/Analyse")

> transFile <-
"RaGene-1_0-st-v1.na27.rn4.transcript.csv1/RaGene-1_0-st-v1.na27.rn4.transcr
ipt.csv"

> probeFile <- "RaGene-1_0-st-v1.probe.tab/RaGene-1_0-st-v1.probe.tab"

> clfFile <- "RaGene-1_0-st-v1.r4.clf/RaGene-1_0-st-v1.r4.clf"

> pgfFile <- "RaGene-1_0-st-v1.r4.pgf/RaGene-1_0-st-v1.r4.pgf"

> pkg <- new("AffyGenePDInfoPkgSeed", author="Anne-Marie Madore",
email="anne-marie.madore.1@ulaval.ca", version="0.0.1",

+ genomebuild="RefSeq April 3, 2007, GenBank® January 25, 2007, Rat Ensembl
transcripts April 3, 2007 ",

+ biocViews="AnnotationData", pgfFile=pgfFile, clfFile=clfFile,
transFile=transFile, probeFile=probeFile)

> makePdInfoPackage(pkg, destDir=".")

Creating package in ./pd.ragene.1.0.st.v1 

loadUnitsByBatch took 50.51 sec

loadAffyCsv took 12.73 sec

loadAffySeqCsv took 57.62 sec

DB sort, index creation took 24.75 sec

[1] TRUE

Warning messages:

1: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL'

2: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL'

 

 

## installing the package in cmd command shell

 

Microsoft Windows [version 6.0.6001]

Copyright (c) 2006 Microsoft Corporation. Tous droits réservés.

 

C:\Users\Anne-Marie Madore>cd c:\Program Files\R\R-2.8.1\bin

 

c:\Program Files\R\R-2.8.1\bin>R CMD INSTALL pd.ragene.1.0.st.v1

installing to 'c:/PROGRA~1/R/R-28~1.1/library'

 

 

---------- Making package pd.ragene.1.0.st.v1 ------------

  adding build stamp to DESCRIPTION

  installing NAMESPACE file and metadata

  installing R files

  installing inst files

  preparing package pd.ragene.1.0.st.v1 for lazy loading

Loading required package: RSQLite

Loading required package: DBI

Loading required package: oligoClasses

Loading required package: Biobase

Loading required package: tools

 

Welcome to Bioconductor

 

  Vignettes contain introductory material. To view, type

  'openVignette()'. To cite Bioconductor, see

  'citation("Biobase")' and for packages 'citation(pkgname)'.

 

  no man files in this package

  installing indices

  installing help

  adding MD5 sums

 

* DONE (pd.ragene.1.0.st.v1)

 

 

## If I run a check (R CMD check pd.ragene.st.v1) I get three warning
messages and one note: 

 

1.       * checking R files for non-ASCII characters ... WARNING 
Found the following files with non-ASCII characters: all.R Portable packages
must use only ASCII characters in their R code, except perhaps in comments.

2.       * checking whether the name space can be loaded with stated
dependencies ... WARNING
Error in initDbConnection() : could not find function "dbConnect" Error:
.onLoad failed in 'loadNamespace' for 'pd.ragene.1.0.st.v1' Execution halted
A namespace must be able to be loaded with just the base namespace loaded:
otherwise if the namespace gets loaded by a saved object, the session will
be unable to start. 
Probably some imports need to be declared in the NAMESPACE file.

3.       * checking R code for possible problems ... NOTE
closeDb: no visible binding for global variable 'dbCon' 

4.       * checking for missing documentation entries ... WARNING
Undocumented code objects: 
pd.ragene.1.0.st.v1 
All user-level objects in a package should have documentation entries. See
the chapter 'Writing R documentation files' in manual 'Writing R
Extensions'.

 

 

## analyzing the package

 

> library("pd.ragene.1.0.st.v1")

> library(oligo)

> library(limma)

> library(genefilter)

Loading required package: survival

> library(geneplotter)

Loading required package: lattice

Loading required package: annotate

Loading required package: xtable

KernSmooth 2.22 installed

Copyright M. P. Wand 1997

> cel.files <- list.celfiles(".", full.names = TRUE)

> basename(cel.files)

 [1] "AD_Ctrl_1.CEL"    "AD_Ctrl_2.CEL"    "AD_Ctrl_3.CEL"
"AD_Ctrl_5.CEL"   

 [5] "AD_Ctrl_6.CEL"    "AD_Traite_10.CEL" "AD_Traite_11.CEL"
"AD_Traite_7.CEL" 

 [9] "AD_Traite_8.CEL"  "AD_Traite_9.CEL" 

> test <- read.celfiles(cel.files)

Platform design info loaded.

> phenoData(test) <- read.AnnotatedDataFrame("phenoData.txt", header = TRUE,
row.name=1)

> class(test)

[1] "GeneFeatureSet"

attr(,"package")

[1] "oligoClasses"

> class(phenoData)

[1] "standardGeneric"

attr(,"package")

[1] "methods"

> eset <- rma(test)

Background correcting

Normalizing

> e <- exprs(eset)

> index1 <- 1:5

> index2 <- 6:10

> d <- rowMeans(e[, index1]) - rowMeans(e[, index2])

> design <- model.matrix(~factor(eset$Key))

> fit <- lmFit(eset, design)

> ebayes <- eBayes(fit)

> sample <- row.names(ebayes)

> Pvalue <- ebayes$p.value[,2]

> Mean1 <-  rowMeans(e[,index1])

> Mean2 <-  rowMeans(e[,index2])

> sd1 <- apply(e[,index1], 1, "sd")

> sd2 <- apply(e[,index2], 1, "sd")

> csv <- read.csv(file="D:/Anne-Marie/Doctorat/puces ADN macrophages/puces
rat/Annie
Dube/Analyse/RaGene-1_0-st-v1.na27.rn4.transcript.header.DOS.csv",head=TRUE,
sep=",")

> all <- merge(csv, Pvalue, by.x="sample", by.y=0, all=T)

> all2 <- merge(all, Mean1, by.x="sample", by.y=0, all=T)

> all3 <- merge(all2, Mean2, by.x="sample", by.y=0, all=T)

> all4 <- merge(all3, sd1, by.x="sample", by.y=0, all=T)

> all5 <- merge(all4, sd2, by.x="sample", by.y=0, all=T)

> all6 <- merge(all5, d, by.x="sample", by.y=0, all=T)

> write.table(data.frame(all6), file="ULTIMETESTtout.xls", sep="\t",
col.names = NA)

> dim(all6)

[1] 240410     24

> 

> # I also try using slightly the same way as I used with affy package

> 

> pd <- read.AnnotatedDataFrame("pheno.txt", header = TRUE, row.names = 1)

> pData(pd)

                 Phenotype

AD_Ctrl_1.CEL      Control

AD_Ctrl_2.CEL      Control

AD_Ctrl_3.CEL      Control

AD_Ctrl_5.CEL      Control

AD_Ctrl_6.CEL      Control

AD_Traite_7.CEL    Traited

AD_Traite_8.CEL    Traited

AD_Traite_9.CEL    Traited

AD_Traite_10.CEL   Traited

AD_Traite_11.CEL   Traited

> a <- read.celfiles(filenames = rownames(pData(pd)), phenoData = pd,
verbose = TRUE)

Platform design info loaded.

> eset <- rma(a)

Background correcting

Normalizing

> exprs.eset <- exprs(eset)

> index1 <- 1:5

> index2 <- 6:10

> d <- (rowMeans(exprs.eset[,index1]) - rowMeans(exprs.eset[,index2]))

> population.groups <- factor (c(rep("Control",5), rep ("Traited",5)))

> design <- model.matrix (~population.groups)

> fit <- lmFit (eset, design)

> fit.eBayes <- eBayes (fit)

> sample <- row.names(fit.eBayes)

> Pvalue <- fit.eBayes$p.value[,2]

> Mean1 <-  rowMeans(e[,index1])

> Mean2 <-  rowMeans(e[,index2])

> sd1 <- apply(e[,index1], 1, "sd")

> sd2 <- apply(e[,index2], 1, "sd")

> csv <- read.csv(file="D:/Anne-Marie/Doctorat/puces ADN macrophages/puces
rat/Annie
Dube/Analyse/RaGene-1_0-st-v1.na27.rn4.transcript.header.DOS.csv",head=TRUE,
sep=",")

> all <- merge(csv, Pvalue, by.x="sample", by.y=0, all=T)

> all2 <- merge(all, Mean1, by.x="sample", by.y=0, all=T)

> all3 <- merge(all2, Mean2, by.x="sample", by.y=0, all=T)

> all4 <- merge(all3, sd1, by.x="sample", by.y=0, all=T)

> all5 <- merge(all4, sd2, by.x="sample", by.y=0, all=T)

> all6 <- merge(all5, d, by.x="sample", by.y=0, all=T)

> write.table(data.frame(all6), file="TESTtout.xls", sep="\t", col.names =
NA)

> dim(all6)

[1] 240410     24

> sessionInfo()

R version 2.8.1 (2008-12-22) 

i386-pc-mingw32 

 

locale:

LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

 

attached base packages:

[1] splines   tools     stats     graphics  grDevices utils     datasets
methods   base     

 

other attached packages:

 [1] geneplotter_1.20.0        annotate_1.20.1           xtable_1.5-4


 [4] lattice_0.17-17           genefilter_1.22.0         survival_2.34-1


 [7] limma_2.16.3              pd.ragene.1.0.st.v1_0.0.1 pdInfoBuilder_1.6.0


[10] oligo_1.6.0               oligoClasses_1.4.0        AnnotationDbi_1.4.2


[13] preprocessCore_1.4.0      affxparser_1.14.2         RSQLite_0.7-1


[16] DBI_0.2-4                 Biobase_2.2.1            

 

loaded via a namespace (and not attached):

[1] grid_2.8.1         KernSmooth_2.22-22 RColorBrewer_1.0-2

 


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