Hi. 

This is a similiar issue reported here  : annotating microarray data with mogene10stv1

So I'm annotating a microarray .CEL data pulled from GEO by an accession number using GEOquery, and am unable to annotate the resultant expression set using BiomaRt (using the respective hg_u133a_2.db).  The error is that I receive all NAs.

The first issue is that I'm unable to use affycoretools to filter the main probes.

qus<-getGEO("GSE30550")[[1]] 

getMainProbes(qus)
Error: The file GPL9188 does not appear to have been processed using the oligo package.
In this case the argument to this function should be the name of the correct pd.info package (e.g., pd.hugene.1.0.st.v1.

traceback()
2: stop(paste("The file", pdinfo, "does not appear to have been processed using",
       "the oligo package.\nIn this case the argument to this function should",
       "be the name of the correct pd.info package (e.g., pd.hugene.1.0.st.v1.\n"),
       call. = FALSE)
1: getMainProbes(qus)

for an attempt with biomaRt

here the affyids are the featureNames(qus)

maRt<-getBM(attributes=c('affy_hg_u133a_2','entrezgene'),filters='affy_hg_u133a_2',values=affyids,mart=ensembl)

maRt[affyids %in% maRt[,1],]   

   affy_hg_u133a   entrezgene
NA             <NA>         NA
NA.1           <NA>         NA
NA.2           <NA>         NA
NA.3           <NA>         NA
NA.4           <NA>         NA
NA.5           <NA>         NA
NA.6           <NA>         NA
NA.7           <NA>         NA
NA.8           <NA>         NA
NA.9           <NA>         NA
NA.10          <NA>         NA
NA.11          <NA>         NA
NA.12          <NA>         NA
NA.13          <NA>         NA
NA.14          <NA>         NA
NA.15          <NA>         NA
NA.16          <NA>         NA
NA.17          <NA>         NA
NA.18          <NA>         NA
NA.19          <NA>         NA
NA.20          <NA>         NA

 

so i'm getting a bunch of control probes returned without any gene names.  and am not able to use the affycoretools

qus
ExpressionSet (storageMode: lockedEnvironment)
assayData: 11961 features, 268 samples
  element names: exprs
protocolData: none
phenoData
  sampleNames: GSM757898 GSM757899 ... GSM758165 (268 total)
  varLabels: title geo_accession ... data_row_count (35 total)
  varMetadata: labelDescription
featureData
  featureNames: 10000_at 10001_at ... 9_at (11961 total)
  fvarLabels: ID Gene_ID Description
  fvarMetadata: Column Description labelDescription
experimentData: use 'experimentData(object)'
Annotation: GPL9188
>

I've checked that the annotation of GPL9188 is corresponding to  hgu133a version 2 chip.   Yet I'm having trouble annotating the correct probes.

The alternate solution is to build the expression set using the affy package, and oligio package, however I was hoping the GEOquery package could build it faster.   any suggestions greatly appreciated.

here's my info

 sessionInfo()
R version 3.2.3 (2015-12-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.3 LTS

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] tools     stats4    parallel  stats     graphics  grDevices utils    
 [8] datasets  methods   base     

other attached packages:
 [1] GEOquery_2.36.0            biomaRt_2.26.1            
 [3] artemisData_0.21           matrixStats_0.50.1        
 [5] artemis_0.42.5             beeswarm_0.2.1            
 [7] SummarizedExperiment_1.0.2 TxDbLite_1.9.100          
 [9] stringdist_0.9.4.1         knitr_1.12                
[11] rtracklayer_1.30.1         ensembldb_1.2.1           
[13] GenomicFeatures_1.22.8     AnnotationDbi_1.32.3      
[15] GenomicRanges_1.22.3       RSQLite_1.0.0             
[17] DBI_0.3.1                  Biobase_2.30.0            
[19] qusage_2.2.0               limma_3.26.5              
[21] GenomeInfoDb_1.6.1         IRanges_2.4.6             
[23] S4Vectors_0.8.7            BiocGenerics_0.16.1       
[25] jsonlite_0.9.19           

loaded via a namespace (and not attached):
 [1] TH.data_1.0-6                colorspace_1.2-6            
 [3] hwriter_1.3.2                estimability_1.1-1          
 [5] qvalue_2.2.2                 futile.logger_1.4.1         
 [7] XVector_0.10.0               interactiveDisplayBase_1.8.0
 [9] mvtnorm_1.0-4                codetools_0.2-14            
[11] splines_3.2.3                R.methodsS3_1.7.0           
[13] DESeq_1.22.1                 geneplotter_1.48.0          
[15] pathview_1.10.1              Rsamtools_1.22.0            
[17] annotate_1.48.0              png_0.1-7                   
[19] R.oo_1.19.0                  graph_1.48.0                
[21] shiny_0.13.0                 httr_1.0.0                  
[23] lsmeans_2.21-1               Matrix_1.2-3                
[25] htmltools_0.3                coda_0.18-1                 
[27] gtable_0.1.2                 reshape2_1.4.1              
[29] ShortRead_1.28.0             Rcpp_0.12.3                 
[31] Biostrings_2.38.3            gdata_2.17.0                
[33] nlme_3.1-123                 stringr_1.0.0               
[35] mime_0.4                     gtools_3.5.0                
[37] XML_3.98-1.3                 erccdashboard_1.4.0         
[39] AnnotationHub_2.2.3          edgeR_3.12.0                
[41] zlibbioc_1.16.0              MASS_7.3-45                 
[43] zoo_1.7-12                   scales_0.3.0                
[45] aroma.light_3.0.0            BiocInstaller_1.20.1        
[47] RBGL_1.46.0                  KEGGgraph_1.28.0            
[49] sandwich_2.3-4               rhdf5_2.14.0                
[51] QuasiSeq_1.0-8               lambda.r_1.1.7              
 

There are no 'main' probes for this array. That is a concept for the WT array series only. In addition, there is no need to use biomaRt to annotate this array. You can use the hgu133a2.db package instead. If you are already using affycoretools, something like

annotation(qus) <- "hgu133a2.db"
library(BiocInstaller)
library(affycoretools)
biocLite("hgu133a2.db")
library(hgu133a2.db)
qus <- annotateEset(qus)

Will populate the featureData slot of the ExpressionSet with Entrez Gene, HUGO symbol, and gene name. And then if you use limma to fit the model, your topTable will get annotated automatically.

okay thank you

I was able to solve using the oligo package as well.    

celFiles<- list.celfiles(getwd(),listGzipped=TRUE)
affyRaw<-read.celfiles(celFiles)
library(pd.hg.u133a.2)
 eset<-rma(affyRaw)

Annot<-data.frame(ACCNUM=sapply(contents(hgu133a2ACCNUM),
paste,
collapse=", "),
SYMBOL=sapply(contents(hgu133a2SYMBOL),paste,
collapse=", "))

my_frame<-data.frame(exprs(eset))

all<-merge(Annot,my_frame,by.x=0,by.y=0,all=T)

heres all the genes

head(all[,1:4])
  Row.names ACCNUM SYMBOL GSM757898.CEL.gz
1 1007_s_at U48705     NA         8.057068
2   1053_at M87338   RFC2         7.490671
3    117_at X51757  HSPA6        10.315676
4    121_at X69699   PAX8         8.606068
5 1255_g_at L36861 GUCA1A         4.249521
6   1294_at L13852     NA         9.783643