I am currently working on this colorectal cancer dataset GSE14333 and I was wondering as to how do I know which samples in this dataset are treated and untreated?
head(GSE14333_PHENO)
X Location DukesStage Age Gender DFSTime DFS_group DFSCens AdjXRT AdjCTX
1 GSM358387 Rectum B 54 M 9.96 poor 0 Y Y
2 GSM358392 Right B 38 F 17.95 poor 1 N Y
3 GSM358395 Right B 78 F 22.02 poor 1 N Y
4 GSM358396 Left B 65 F 22.38 poor 0 Y Y
5 GSM358397 Left B 65 F 22.38 poor 0 Y Y
6 GSM358399 Left B 56 F 25.21 poor 0 Y Y
I am a beginner, would appreciate any help in this regard. Many thanks!
•
written
by
bio94 •
There are Expression data from 290 primary colorectal cancers. Sample description is here
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14333
Click on your GSM* to know more about them
It would be tedious to click on 290 samples. It is also not clear if the information OP is looking for is included in GEO records. Nearest thing to sample info I see is this
Location: Right; DukesStage: A; Age_Diag: 78; Gender: M; DFS_Time: 3.64; DFS_Cens: 1; AdjXRT: N; AdjCTX: N
Do you know which part refers to treated/untreated?
For all samples, patient demography can be had from series matrix file, in one go.
series summary:
Samples were taken from colorectal cancers in surgically resected specimens in 290 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133Plus 2.0 arrays. The training set of our prognosis classifier included the stage A and D samples. Validation used our stage B and C samples.
series overall design:
mRNA from 290 primary colorectal tumour samples were extracted and hybridized to HG-U133Plus 2.0 expression arrays. The MAS5.0 procedure was used to make calls of expression. Data from the Stage A and D samples were quantile normalized and used with microarray data from the expO set to build a classifier. The Stage B and C samples were were quantile normalized with reference to a training set prior to application of our prognosis classifier.
Actually, I wanted to point out to OP two things by above reply. 1) You can always get the full information of samples from GEO page, as sometimes gleaning this info from publication is difficult and also 2) GEO page can serve as a cross-reference to check your metadata.
Do you know which part refers to treated/untreated?
I didn't find this information by cursory a look, and I had also the doubt that perhaps the samples are not annotated for this info at all. However, my intention was to nudge OP to carefully look into the page - again to make evident that all the study level info are registered as GSE* and sample level info are in GSM*.
It would be tedious to click on 290 samples.
:) Never expected OP to that. Since s/he posted only 6 samples, I thought that by looking at the info of some of the samples, s/he can confidently know if this info was ever present at the submission time, and in which metadata
Log in to answer this question.
Have you looked to see if you can find this information in paper/supplemental information (more than likely).
Note: There is no need to include
#to create tags on Biostars. Just bare words are used astags.Sure, I'll have a look at that. Yes! I almost forgot that I included #. My mistake.
Treated with what? Radio or chemo? What do you think the lasts two columns are?
I believe they are Adjuvant Radiotherapy and Adjuvant chemotherapy. So If It's a YES for any one of these two columns, I consider them as TREATED. If a NO for both the columns I consider them as UNTREATED?
That seems to correspond to last two columns and would logically be right. You should have included this info in the original post if you knew about it then.
but does that mean the patient was treated during follow-up, or does it mean the patient was treated prior to resection?
bio94 : Please don't delete posts when they have received comments/answers.