Dear everyone,

im a PhD-Student with zero background in bioinformatics and R but I have to analyze the expression of my Protein of interest in an online available Affymetrix Array. So what comes next is completely self-taught: I downloaded the RAW-Files (.CEL) and used this code in R:

> library(oligo)
> celFiles = list.celfiles()
> affyRaw <- read.celfiles(celFiles)
 > eset <- rma(affyRaw)

By using:

>write.exprs(eset,file="data.txt")

I get a text-file with my "normalized" Data, right? But now I have no idea how I can annotate my Data? I loaded the package: pd.hugene.2.0.st but I can't figure out, how to work this out...

Output of >sessioninfo()

> sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.0.1

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

locale:
[1] de_DE.UTF-8/de_DE.UTF-8/de_DE.UTF-8/C/de_DE.UTF-8/de_DE.UTF-8

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

other attached packages:
 [1] pd.hugene.2.0.st_3.14.1 DBI_1.1.3               RSQLite_2.2.17          oligo_1.60.0            Biostrings_2.64.1       GenomeInfoDb_1.32.4    
 [7] XVector_0.36.0          IRanges_2.30.1          S4Vectors_0.34.0        Biobase_2.56.0          oligoClasses_1.58.0     BiocGenerics_0.42.0    

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.9                  compiler_4.2.1              BiocManager_1.30.18         MatrixGenerics_1.8.1        bitops_1.0-7               
 [6] iterators_1.0.14            tools_4.2.1                 zlibbioc_1.42.0             bit_4.0.4                   memoise_2.0.1              
[11] preprocessCore_1.58.0       lattice_0.20-45             ff_4.0.7                    pkgconfig_2.0.3             rlang_1.0.5                
[16] Matrix_1.5-1                foreach_1.5.2               cli_3.4.0                   DelayedArray_0.22.0         fastmap_1.1.0              
[21] GenomeInfoDbData_1.2.8      affxparser_1.68.1           vctrs_0.4.1                 bit64_4.0.5                 grid_4.2.1                 
[26] blob_1.2.3                  codetools_0.2-18            matrixStats_0.62.0          GenomicRanges_1.48.0        splines_4.2.1              
[31] SummarizedExperiment_1.26.1 RCurl_1.98-1.8              cachem_1.0.6                crayon_1.5.1                affyio_1.66.0

Thank you so much!

The simple solution is

library(affycoretools)
library(hugene20sttranscriptcluster.db)
eset <- annotateEset(eset, hugene20sttranscriptcluster.db)

And then after you fit the model using limma your topTable output will be automatically annotated with the Gene ID, symbol, and gene name. You can add other things in as well, but those are the defaults.

I would normally not do something like write.exprs because what are you going to do with those data that is more sophisticated than fitting models using limma? You can always fit the model and then output the entire topTable to Excel if that's your jam, but usually I would generate an HTML document and use Glimma to make an interactive plot of the data which people seem to like bigly.

Thank you so much for taking the time!

I just want to look at one specific gene and see how It is expressed in different tumor grades. So I wanted to avoid fitting a model and using limma...

By using ur solution:

library(affycoretools)
library(hugene20sttranscriptcluster.db)
eset <- annotateEset(eset, hugene20sttranscriptcluster.db)

I get a perfect table with the SPOT_ID and the expression value. How do I get the annotation with the Gene_ID, symbol etc. without using limma?

I was thinking of a table like this:

k <- head(keys(hugene20sttranscriptcluster.db, keytpye="PROBEID"))
> select (hugene20sttranscriptcluster.db, keys=k, columns=c("SYMBOL","GENENAME"), keytype="PROBEID")

And how do I extract this as a text file?

Thank you so much!