[R] you are making it far too difficult

[Richard M. Heiberger]

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 using 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 using kuleuven.be> wrote:
>
> > Unpack these files.
> >
> > F
> >
> >
>
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>
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