This is the error I keep getting

Error in .testForValidKeys(x, keys, keytype, fks) : 
  None of the keys entered are valid keys for 'PROBEID'. Please use the keys method to see a listing of valid arguments.

This is what the featureNames look like for the filltered

> View(dorsey_manfiltered)
> featureNames(dorsey_manfiltered)
   [1] "1007_s_at"    "1053_at"      "117_at"       "121_at"       "1255_g_at"    "1294_at"      "1316_at"     
   [8] "1320_at"      "1405_i_at"    "1431_at"      "1438_at"      "1487_at"      "1494_f_at"    "1552256_a_at"
  [15] "1552257_a_at" "1552258_at"   "1552261_at"   "1552263_at"   "1552264_a_at" "1552266_at"   "1552269_at"  
  [22] "1552271_at"   "1552272_a_at" "1552274_at"   "1552275_s_at" "1552276_a_at" "1552277_a_at" "1552278_a_at"

d

orsey_medians <- rowMedians(Biobase::exprs(dorsey_eset))
#I guess threshold would be 1, graph looks differen tho
man_threshold <- 1
hist_res <- hist(dorsey_eset, 100, col = "red", freq = FALSE, 
                 main = "Histogram of the median intensities", 
                 border = "antiquewhite4",
                 xlab = "Median intensities")
abline(v = man_threshold, col = "coral4", lwd = 2)

#Transcripts that do not have intensities larger 
#than the threshold in at least as many arrays as the smallest experimental group are excluded.

#In order to do so, we first have to get a list with the number of samples (=arrays) 
#(no_of_samples) in the experimental groups:
no_of_samples <- 
  table(paste0(pData(dorsey_eset)$FactorValue..sample.type., "_", 
               pData(dorsey_eset)$FactorValue..age.))
no_of_samples 

samples_cutoff <- min(no_of_samples)

idx_man_threshold <- apply(Biobase::exprs(dorsey_eset), 1,
                           function(x){
                             sum(x > man_threshold) >= samples_cutoff})
#After filtering out the transcripts that intensities are not greater than thresheold in 
#at least 1 array can see how many genes are filtered out(54675)
table(idx_man_threshold)
#subset expression set to only include those who pass the filtering
dorsey_manfiltered <- subset(dorsey_eset, idx_man_threshold)

featureNames(dorsey_manfiltered)
library(org.Hs.eg.db)
library(AnnotationDbi)
#Before we continue with the linear models for microarrays and 
#differential expression, we first add “feature data”, i.e. annotation information to the transcript cluster 
#identifiers stored in the featureData of our ExpressionSet:
anno_dorsey <- AnnotationDbi::select(hugene10sttranscriptcluster.db,
                                       keys = (featureNames(dorsey_manfiltered)),
                                       columns = c("SYMBOL", "GENENAME"),
                                       keytype = "PROBEID")

anno_dorsey <- subset(anno_dorsey, !is.na(SYMBOL))`enter code here`