Entering edit mode
2.8 years ago
gonzalezb549
•
0
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`
Can you show how you normalised the data?, i.e., the
rma()
orgcrma()
command. Please also confirm the array type and version.It's possible that you need
hugene10stprobeset.db
I used the rma() The array is an expressionset