GDCquery_clinic not working for TCGA projects

[hnsc-a11y]

I tried to download clinical data from TCGA projects but it returned an error message (please see below). It happened for various different TCGA tumor types.

clinical_brca <- GDCquery_clinic("TCGA-BRCA", type = "clinical")
Error in set(x, j = name, value = value) :
Supplied 1098 items to be assigned to 1343 items of column 'submitter_id'. If you wish to 'recycle' the RHS please use rep() to make this intent clear to readers of your code.

clinical_hnsc <- GDCquery_clinic("TCGA-HNSC", type = "clinical")
Error in set(x, j = name, value = value) :
Supplied 528 items to be assigned to 768 items of column 'submitter_id'. If you wish to 'recycle' the RHS please use rep() to make this intent clear to readers of your code.

clinical_gbm <- GDCquery_clinic("TCGA-GBM", type = "clinical")
Error in set(x, j = name, value = value) :
Supplied 617 items to be assigned to 1175 items of column 'submitter_id'. If you wish to 'recycle' the RHS please use rep() to make this intent clear to readers of your code.

Any chance you could look into this issue? Thanks.

Version: 2.32.0

[SNN0]

I have the same problem

[tiagochst]

Hi,

Thank you for the bug report. It seems there were changes in the API/data retrieved that broke the code.
Could you reinstall the devel version from GitHub and try it again.

If anyone finds other issues, please let me know. I will need to rewrite the code due to those changes.

remotes::install_github("https://github.com/BioinformaticsFMRP/TCGAbiolinks",ref = "devel")

[SNN0]

Hi,

The function is working, and I can access the clinical data. For example, I retrieved the clinical data for the BRCA cohort, but there are too many NA values in days_to_last_follow_up. I have worked with this cohort before, and it seems like there weren’t this many NA values. Could there be an error here?

[tiagochst]

It seems to be an issue on the API side. I have null for days_to_last_follow_up for all the TCGA-GBM samples. [image: Screenshot 2025-01-31 at 2.54.32 PM.png] I will send an email to GDC regarding this issue.

…

On Fri, Jan 31, 2025 at 2:49 PM SNN0 ***@***.***> wrote: Hi, The function is working, and I can access the clinical data. For example, I retrieved the clinical data for the BRCA cohort, but there are too many NA values in days_to_last_follow_up. I have worked with this cohort before, and it seems like there weren’t this many NA values. Could there be an error here? — Reply to this email directly, view it on GitHub <#639 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABDQ6IWZUX4Q33WIAOVSKL2NPHVRAVCNFSM6AAAAABWIGJ64WVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDMMRYGI2TCMRWGY> . You are receiving this because you commented.Message ID: ***@***.***>

[SNN0]

I really hope this issue gets resolved soon because I don’t want my project to be delayed. Do you know of any other way to access this data? I have written many of my functions based on this output. Also, can we manually access this data from the GDC portal in the same way? @tiagochst

[tiagochst]

I just got some answers from GDC. I still need to check which changes need to be made. 1. The GDC just deployed our latest data release, in which almost all of the TCGA clinical data was indexed in the API instead of being largely available in the supplemental files. 2. I think the days_to_last_followup field has been moved to the follow_up node as "days_to_followup". Add "follow_up" to your expand fields and you should see it. I think you will need to add an extra step to determine which follow_up has the largest value. This data should be the same one downloaded in this TSV file if you want to download manually. [image: Screenshot 2025-01-31 at 5.03.07 PM.png]

…

On Fri, Jan 31, 2025 at 3:41 PM SNN0 ***@***.***> wrote: I really hope this issue gets resolved soon because I don’t want my project to be delayed. Do you know of any other way to access this data? I have written many of my functions based on this output. Also, can we manually access this data from the GDC portal in the same way? @tiagochst <https://github.com/tiagochst> — Reply to this email directly, view it on GitHub <#639 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABDQ6KNWH3Z2Z2LAN3YQJL2NPNWPAVCNFSM6AAAAABWIGJ64WVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDMMRYGM3DGMBQGI> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[hnsc-a11y]

@tiagochst Thank you so much for the prompt response and the effort in resolving the issue!

I think I may need to download the data manually for now, but for some reason I can't see this screenshot image from your previous post. Any chance you can upload it again? Thanks!

This data should be the same one downloaded in this TSV file if you want to
download manually.
[image: Screenshot 2025-01-31 at 5.03.07 PM.png]

[tiagochst]

@hnsc-a11y

[femiogundare]

Hi,

I'm facing the same issue.

[ramyaPurkanti]

Hello all,

I just found the columns paper_Follow.up.days and paper_Days.to.death in the coldata of the summarised experiment object we get as a result of GDCPrepare (together with many other clinical data attributes).

library(TCGAbiolinks)
query_paad_all <- GDCquery(
  project = "TCGA-PAAD",
  data.category = "Transcriptome Profiling",
  experimental.strategy = "RNA-Seq",
  workflow.type = "STAR - Counts",
  data.type = "Gene Expression Quantification",
  sample.type = "Primary Tumor",
  access = "open")
tcga_paad_data <- GDCprepare(query_paad_all, summarizedExperiment = TRUE, directory = TCGAbiolinks_dir)

tcga_paad_coldata <- colData(tcga_paad_data) %>%  as.data.frame()
tcga_paad_coldata$paper_Follow.up.days
tcga_paad_coldata$paper_Days.to.death

Can someone confirm if this is equivalent to the clinical data we used to pull separately using GDCquery_clinic ? I sadly did not save the Rdataframes I pulled earlier so cannot check myself.

Thanks,
Ramya

[tiagochst]

Hi Ramya, Every column with prefix paper_ in metadata pulled from supplemental files from the TGCA analysis groups articles. If the clinical data continues to be updated, they will be different from what was published years ago.

…

On Mon, Feb 3, 2025 at 11:49 AM Ramya Purkanti ***@***.***> wrote: Hello all, I just found the columns *paper_Follow.up.days* and *paper_Days.to.death* in the coldata of the summarised experiment object we get as a result of GDCPrepare (together with many other clinical data attributes). ` library(TCGAbiolinks) query_paad_all <- GDCquery( project = "TCGA-PAAD", data.category = "Transcriptome Profiling", experimental.strategy = "RNA-Seq", workflow.type = "STAR - Counts", data.type = "Gene Expression Quantification", sample.type = "Primary Tumor", access = "open") tcga_paad_data <- GDCprepare(query_paad_all, summarizedExperiment = TRUE, directory = TCGAbiolinks_dir) tcga_paad_coldata <- colData(tcga_paad_data) %>% as.data.frame() tcga_paad_coldata$paper_Follow.up.days tcga_paad_coldata$paper_Days.to.death ` Can someone confirm if this is equivalent to the clinical data we used to pull separately using GDCquery_clinic ? I sadly did not save the Rdataframes I pulled earlier so cannot check myself. Thanks, Ramya — Reply to this email directly, view it on GitHub <#639 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABDQ6IEI74QRS6FZIYLIYT2N6MYLAVCNFSM6AAAAABWIGJ64WVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDMMZRGUZTMOJUHA> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[YeHW]

I just got some answers from GDC. I still need to check which changes need
to be made.

1. The GDC just deployed our latest data release, in which almost all of
   the TCGA clinical data was indexed in the API instead of being largely
   available in the supplemental files.
2. I think the days_to_last_followup field has been moved to the
   follow_up node as "days_to_followup". Add "follow_up" to your expand
   fields and you should see it. I think you will need to add an extra step
   to determine which follow_up has the largest value.

This data should be the same one downloaded in this TSV file if you want to
download manually.
[image: Screenshot 2025-01-31 at 5.03.07 PM.png]
…

On Fri, Jan 31, 2025 at 3:41 PM SNN0 @.***> wrote:
I really hope this issue gets resolved soon because I don’t want my
project to be delayed. Do you know of any other way to access this data? I
have written many of my functions based on this output. Also, can we
manually access this data from the GDC portal in the same way? @tiagochst
https://github.com/tiagochst

—
Reply to this email directly, view it on GitHub
<#639 (comment)>,
or unsubscribe
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.
You are receiving this because you were mentioned.Message ID:
@.***>

Hi @tiagochst,

I faced the same issue with TCGA-DLBC project, all "days_to_last_follow_up" are NA.
I'm new to TCGAbiolinks - How exactly should I add "follow_up" to expand fields?
Is it to say I should download tsv/json from GDC Data Portal, then use the max value of "days_to_follow_up" column for each case_submitter_id id in the "follow_up.tsv"?

Thanks!

[ramyaPurkanti]

An update: I pulled out the follow_ups node details but the follow_ups.days_to_follow_up does not contain a single integer, it's for each follow up event. I could not find a ready made column for days_to_last_follow_up (the one within diagnoses is all NA) anywhere. I haven't yet checked whether if we take the max of all values in follow_ups.days_to_follow_up column, if it matches the value we get by downloading manually.

In case someone wants to check up, the commands to pull out the clinical data are:

library(GenomicDataCommons)
metadata <- cases() %>%
    GenomicDataCommons::filter( project.project_id == 'TCGA-GBM') %>%
    GenomicDataCommons::select(default_fields('cases'), "demographic.vital_status", "demographic.days_to_death", "diagnoses.days_to_last_follow_up", GenomicDataCommons::grep_fields('cases', 'follow'))) %>%
    results_all()

[ptranvan]

Hello,

Is there any plan to reintegrate the field days_to_last_follow_up when getting data with:

query <- GDCquery(
  project = id,
  data.category = "Transcriptome Profiling", 
  data.type = "Gene Expression Quantification",
  experimental.strategy = "RNA-Seq",
  access = "open",
  workflow.type = "STAR - Counts"
)

data_full <- GDCprepare(query, summarizedExperiment = TRUE)
colnames(colData(data_full))

Thanks.