Mr. Heiberger,
I followed your argument and it works. I received the same data. And yes,
ICGC breakes their datasets into separate files based on data type. Thank
you for the pointer on selecting all 50 rows, as I assumed that the
entirety of gene expression data within the data set would be downloaded
through the process you followed, as it does when directly downloading the
file via a tsv.gz download.
On Thu, Dec 27, 2018 at 4:05 PM Richard M. Heiberger <rmh at temple.edu>
wrote:
> 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 <
> spbrackett20 at 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.calboli at kuleuven.be> wrote:
>>
>> > Unpack these files.
>> >
>> > F
>> >
>> >
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
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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.
>>
>
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