Dear list

I came across an error when trying to run the example in the virtualArray vignette.

(I saw another mail in the support site which describe the same error with no replies)

I would appreciate if someone could help me to solve it

Thanks

Mali

> library("GEOquery")
> GSE23402 <- getGEO("GSE23402",GSEMatrix=T,AnnotGPL=FALSE)
> GSE26428 <- getGEO("GSE26428",GSEMatrix=T,AnnotGPL=FALSE)
> GSE23402 <- GSE23402[[1]][,1:24]
> GSE26428 <- GSE26428[[1]]
> exprs(GSE23402) <- log2(exprs(GSE23402))
> exprs(GSE26428) <- (exprs(GSE26428)/20*16)
> annotation(GSE23402) <- "hgu133plus2"
> annotation(GSE26428) <- "hgug4112a"
> my_virtualArrays <- NULL
> my_virtualArrays$iPSC_hESC_noBatchEffect <- virtualArrayExpressionSets()

Loading required package: BiocParallel
Now preprocessing raw data of GSE23402: Loading annotations...
Usinghgu133plus2as Bioconductor annotation package for datasetGSE23402.
Loading required package: hgu133plus2.db
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: GenomeInfoDb
Loading required package: S4Vectors
Attaching package: S4Vectors
The following object is masked from package:plyr:

   rename

Loading required package: IRanges
Attaching package: IRanges
The following object is masked from package:plyr:

    desc

Attaching package: AnnotationDbi
The following object is masked from package:GenomeInfoDb:

    species

Loading required package: org.Hs.eg.db
Loading required package: DBI

Now preprocessing raw data of GSE23402: Collapsing expression values to their median...
Using identifier as id variables
Now preprocessing raw data of GSE23402: Annotating expression values with SYMBOL...

Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x),  : 

  'data' must be of a vector type, was 'NULL'



> sessionInfo()

R version 3.1.2 (2014-10-31)

Platform: x86_64-unknown-linux-gnu (64-bit)


locale:

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              

 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    

 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   

 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 

 [9] LC_ADDRESS=C               LC_TELEPHONE=C            

[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       


attached base packages:

[1] stats4    parallel  stats     graphics  grDevices utils     datasets 

[8] methods   base     


other attached packages:

 [1] hgu133plus2.db_3.0.0  org.Hs.eg.db_3.0.0    RSQLite_1.0.0        

 [4] DBI_0.3.1             AnnotationDbi_1.28.1  GenomeInfoDb_1.2.3   

 [7] IRanges_2.0.0         S4Vectors_0.4.0       BiocParallel_1.0.0   

[10] GEOquery_2.32.0       virtualArray_1.8.0    preprocessCore_1.28.0

[13] plyr_1.8.1            Biobase_2.26.0        BiocGenerics_0.12.1  


loaded via a namespace (and not attached):

 [1] affy_1.44.0          affyio_1.34.0        affyPLM_1.42.0      

 [4] base64enc_0.1-2      BatchJobs_1.5        BBmisc_1.8          

 [7] BiocInstaller_1.16.1 Biostrings_2.34.0    brew_1.0-6          

[10] checkmate_1.5.0      codetools_0.2-9      digest_0.6.4        

[13] fail_1.2             foreach_1.4.2        gcrma_2.38.0        

[16] grid_3.1.2           iterators_1.0.7      lattice_0.20-29     

[19] outliers_0.14        quadprog_1.5-5       Rcpp_0.11.3         

[22] RCurl_1.95-4.3       reshape2_1.4         sendmailR_1.2-1     

[25] splines_3.1.2        stringr_0.6.2        tools_3.1.2

The virtualArray package is no longer part of Bioconductor (as of version 3.0). You have BioC 3.0 installed, as well as virtualArray, which is from 2.14, so there may well be more than one thing wrong with your installation. I would recommend doing

library(BiocInstaller)

biocValid()

And following the recommendations to get a coherent BioC installation. There is nothing wrong per se with having a mixture of packages, but there is no guarantee that they will all work in harmony, and if they don't (which seems to be the case here), we don't provide any support.

That said, if you want to do meta-analysis using different platforms, there are still supported packages in Bioconductor that are directed towards that sort of thing. I would recommend taking a look at GeneMeta, which I recently used to analyze a bunch of different GEO data sets (a combination of one and two color arrays), and found to be quite useful. Other choices are categoryCompare, metaArray and possibly RankProd.