Question: Opening Illumina HT12 V3.0 Data from GEO
gravatar for FL512
6 weeks ago by
FL5120 wrote:

I was essentially doing the same things posted previously.



Following the note posted on 1, I have successfully downloaded the data of my interest.

data <- getGEO("GSE32894")[[1]]

Unfortunately, I got stuck when I was trying to read "GSE32894" with limma.

idata <- read.ilmn("GSE32894_non-normalized_308UCsamples.txt",probeid = "PROBE_ID",expr="SKBR")

The error shows as follows;

Error in readGenericHeader(fname, columns = expr, sep = sep) : 
  Specified column headings not found in file

I looked into the documentation (, none of them worked out.

It should be great if you can give me any kind of suggestion to fix this problem.

Thank you.

normalization limma geo • 79 views
ADD COMMENTlink modified 5 weeks ago • written 6 weeks ago by FL5120

In the above the quotation marks " are not correct; what is the actual command that you used?

ADD REPLYlink written 6 weeks ago by Martin Morgan ♦♦ 24k

Yes, you right. I am sorry for any confusion caused. I will change from reading to opening Illumina HT12 V3.0 Data from GEO.

ADD REPLYlink written 5 weeks ago by FL5120

OP has copied Mark Dunning's code (which was for a specific dataset) from I reformated OP's question before, now I've removed the extra quote mark as well.

ADD REPLYlink modified 5 weeks ago • written 5 weeks ago by Gordon Smyth39k
Answer: Reading Illumina HT12 V3.0 Data from GEO
gravatar for James W. MacDonald
5 weeks ago by
United States
James W. MacDonald51k wrote:

In your first code chunk you are reading in the wrong GSE (GSE32849), which is a CHiP-Chip experiment, rather than the one you want. In the second case, you have a text file containing something that isn't what you think it is:

sed -n '5p' GSE32894_non-normalized_308UCsamples.txt | sed 's/\t/\n/g' | head

You are probably better off just using the data you get from getGEO:

 z <- getGEO("GSE32894")[[1]]
> z
ExpressionSet (storageMode: lockedEnvironment)
assayData: 24402 features, 308 samples 
  element names: exprs 
protocolData: none
  sampleNames: GSM814052 GSM814053 ... GSM814359 (308 total)
  varLabels: title geo_accession ... tumor_stage:ch1 (55 total)
  varMetadata: labelDescription
  featureNames: ILMN_1343291 ILMN_1343295 ... ILMN_2415979 (24402
  fvarLabels: ID nuID ... GB_ACC (30 total)
  fvarMetadata: Column Description labelDescription
experimentData: use 'experimentData(object)'
  pubMedIds: 22553347 
Annotation: GPL6947 
> pData(z)[1:5,54:55]
          tumor_grade:ch1 tumor_stage:ch1
GSM814052              G3              T2
GSM814053              G2              T2
GSM814054              G2              T1
GSM814055              G2              T1
GSM814056              G3             T3b

> table(pData(z)[,54:55])
tumor_grade:ch1 T1 T2 T2a T2b T3 T3b T4a Ta Tx
             G1  0  0   0   0  0   0   0 48  0
             G2 35  9   1   0  1   0   0 56  1
             G3 61 73   0   2  0   5   1 11  1
             G4  1  0   0   0  0   0   0  0  0
             Gx  0  0   0   0  0   1   0  1  0

You can just use limma directly on that ExpressionSet, based on whatever phenotypic groups you care to compare.

ADD COMMENTlink written 5 weeks ago by James W. MacDonald51k

I am sorry James, it was a type, should be GSE32894 as you mentioned. So what if I just want to have normalized data, what am I supposed to do? Because I would like to see a big picture rather than the comparison of specific genes for now.

ADD REPLYlink modified 5 weeks ago • written 5 weeks ago by FL5120

Dear James, I have made a decision to use a series matrix file. I do keep in mind the way how to perform the analysis you showed here. Thank you very much for all you have done for me.

ADD REPLYlink written 5 weeks ago by FL5120
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