Dear list,

I'm analyzing data obtained using the HuGene1.0-st arrays from affymetrix.

I'm interested in a particular set of genes. Two of these genes are not present in the results if I filter out probes with missing Entrez IDs using nsFilter. However, I think that these two genes (PER1 and CSNK1E) actually have an Entrez ID and should not be filtered out. The only way I obtain them in my results is if I don't apply any kind of filter with nsFilter. Do you think I'm doing something wrong with the annotation? This is the code I'm using and the output of sessionInfo(). Thank you so much for your kind help.

exp.data <- read.celfiles(filenames=list.celfiles(full.names=TRUE, dataDir))
phenoData <- read.table(file.path(dataDir ,"pheno_BD_CT.txt"), sep="\t", header=TRUE)
row.names(phenoData) <- sampleNames(exp.data)
pd <- AnnotatedDataFrame(data=phenoData)
phenoData(exp.data) <- pd
eset <- rma(exp.data)
subs <- grep("CT", phenoData(exp.data)$Phenotype)
eset.subs <- eset[,c(subs)]
annotation(eset.subs) <- "hugene10sttranscriptcluster.db"
esetf.subs <- nsFilter(eset.subs, require.entrez=TRUE, remove.dupEntrez=FALSE, var.filter=FALSE)
express <- esetf.subs$eset

> esetf.subs
$eset
ExpressionSet (storageMode: lockedEnvironment)
assayData: 19777 features, 20 samples 
  element names: exprs 
protocolData
  rowNames: 14(1015)_(HuGene-1_0-st-v1).CEL 21(1707)_(HuGene-1_0-st-v1).CEL ...
    9(1168)_(HuGene-1_0-st-v1).CEL (20 total)
  varLabels: exprs dates
  varMetadata: labelDescription channel
phenoData
  rowNames: 14(1015)_(HuGene-1_0-st-v1).CEL 21(1707)_(HuGene-1_0-st-v1).CEL ...
    9(1168)_(HuGene-1_0-st-v1).CEL (20 total)
  varLabels: FileName Response ... Analysis (5 total)
  varMetadata: labelDescription
featureData: none
experimentData: use 'experimentData(object)'
Annotation: hugene10sttranscriptcluster.db 

$filter.log
$filter.log$numRemoved.ENTREZID
[1] 13520

> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] pd.hugene.1.0.st.v1_3.14.1           RSQLite_1.0.0                       
 [3] DBI_0.5                              hugene10sttranscriptcluster.db_8.4.0
 [5] org.Hs.eg.db_3.3.0                   AnnotationDbi_1.34.4                
 [7] genefilter_1.54.2                    oligo_1.36.1                        
 [9] Biostrings_2.40.2                    XVector_0.12.1                      
[11] IRanges_2.6.1                        S4Vectors_0.10.3                    
[13] limma_3.28.18                        oligoClasses_1.34.0                 
[15] Biobase_2.32.0                       BiocGenerics_0.18.0                 
[17] mvtnorm_1.0-5                       

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.6                BiocInstaller_1.22.3       GenomeInfoDb_1.8.3        
 [4] iterators_1.0.8            tools_3.3.1                zlibbioc_1.18.0           
 [7] bit_1.1-12                 tibble_1.1                 annotate_1.50.0           
[10] preprocessCore_1.34.0      lattice_0.20-33            ff_2.2-13                 
[13] Matrix_1.2-6               foreach_1.4.3              dplyr_0.5.0               
[16] affxparser_1.44.0          grid_3.3.1                 R6_2.1.2                  
[19] XML_3.98-1.4               survival_2.40-1            magrittr_1.5              
[22] codetools_0.2-14           splines_3.3.1              GenomicRanges_1.24.2      
[25] assertthat_0.1             SummarizedExperiment_1.2.3 xtable_1.8-2              
[28] sandwich_2.3-4             zoo_1.7-14                 affyio_1.42.0             
> 

The short answer is "don't use nsFilter". I wouldn't even recommend filtering based on whether or not a probeset has an Entrez Gene ID, but that's just me. If you wanted to do something like that you could just do

library(affycoretools)
eset <- annotateEset(eset, hugene10sttranscriptcluster.db)
eset.sub <- eset[!is.na(fData(eset)$ENTREZID),]