I downloaded the Donors dataset
https://dcc.icgc.org/search?filters=%7B%22donor%22:%7B%22projectId%22:%7B%22is%22:%5B%22GBM-US%22%5D%7D,%22availableDataTypes%22:%7B%22is%22:%5B%22pexp%22%5D%7D%7D%7D
by clicking "Export table as TSV".
Then I read it with
donors <- read.delim("~/Downloads/donors_2018_12_27_03_52_03.tsv")
Here is the transcript.
> donors <- read.delim("~/Downloads/donors_2018_12_27_03_52_03.tsv")
> donors
Donor.ID Project.Code Primary.Site Gender Age.at.Diagnosis
1 DO10892 GBM-US Brain Female 45
2 DO12328 GBM-US Brain Male 56
3 DO11657 GBM-US Brain Female 73
4 DO13510 GBM-US Brain Female 63
5 DO12670 GBM-US Brain Female 63
6 DO11501 GBM-US Brain Female 59
7 DO13809 GBM-US Brain Female 74
8 DO13647 GBM-US Brain Male 56
9 DO11645 GBM-US Brain Male 73
10 DO14145 GBM-US Brain Female 85
Tumor.Stage.at.Diagnosis Survival.Time..days. SSM CNSM STSM SGV
METH.A
1 NA NA True True False False
True
2 NA 154 True True False False
True
3 NA NA True True False False
True
4 NA 1448 True True False False
True
5 NA 772 True True False False
True
6 NA NA True True False False
True
7 NA 213 True True False False
True
8 NA 383 True True False False
True
9 NA 113 True True False False
True
10 NA 94 True True False False
True
METH.S EXP.A EXP.S PEXP miRNA.S JCN Mutations Mutated.Genes
1 False True True True False False 269 392
2 False True False True False False 192 263
3 False True False True False False 128 209
4 False True True True False False 130 199
5 False True True True False False 142 194
6 False True True True False False 129 190
7 False True False True False False 130 178
8 False True False True False False 116 175
9 False True False True False False 125 174
10 False True True True False False 108 169
>
I don't know how to get the download of the whole file. It looks like you
could page through it with the page menu at the bottom of the webpage. If
you do that, set it for 50 at a time instead of the default 10.
For the Genes and the two types of Mutation files, it will be more nuisance
this way because there are about 10000 rows for each of those three files,
thus about 200 of these statements per dataset.
I think it is time to move to the bioconductor list for specific guidance
on this type of dataset.
On Thu, Dec 27, 2018 at 3:28 PM Spencer Brackett <
spbracket...@saintjosephhs.com> wrote:
> Mr. Calboli,
>
> After beginning to unpack the GBM file you sent me via directly importing
> it unit my console, I received the following:
>
> View(GBM_PEXP.tsv)
>
> **Note that I named the file GBM_PEXP.tsv)**
>
> Upon downloading, my script now contains a 2 by 2 table, with the x
> column still containing encoded script. As for my Data summary to the
> right, this new file reports that 2 objects are acting upon 1 variable.
> How should I proceed?
>
> -Spencer
>
> On Thu, Dec 27, 2018 at 3:12 PM Federico Calboli <
> federico.calb...@kuleuven.be> wrote:
>
> > Unpack these files.
> >
> > F
> >
> >
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
