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Job request: 11135

Organisation:
The UK Renal Registry
Workspace:
renal-short-data-report
ID:
ilnenf6du66twvjj
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Shalini Santhakumaran requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level various outputs were written to. Researchers can never directly view outputs marked as highly_sensitive ; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: "3.0"

expectations:
  population_size: 1000

actions:

  generate_study_population:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition
      --index-date-range "2019-01-01 to 2021-01-01 by month"
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input*.csv.gz

  generate_study_population_2:
   run: cohortextractor:latest generate_cohort 
     --study-definition study_definition 
     --index-date-range "2021-02-01 to 2022-07-01 by month" 
     --output-format csv.gz
   outputs:
     highly_sensitive:
       cohort: output/inpu*.csv.gz

  generate_study_population_ukrr_ethnicity:
    run: cohortextractor:latest generate_cohort 
      --study-definition study_definition_ukrr_ethnicity
      --output-dir=output
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_ukrr_ethnicity.csv.gz

  join_cohorts:
    run: >
      cohort-joiner:v0.0.46
        --lhs output/input_20*.csv.gz
        --rhs output/input_ukrr_ethnicity.csv.gz
        --output-dir output/joined
    needs: [generate_study_population, generate_study_population_2, generate_study_population_ukrr_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/joined/input_20*.csv.gz

  generate_study_population_paeds:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_paeds
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_paeds.csv.gz


  generate_table_1:
    run: python:latest python analysis/scripts/table_1.py --study_def_paths="output/joined/input_*.csv.gz" --demographics="age_band,sex,region,imd,ethnicity"
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        counts: output/table_1.csv
        at_risk: output/table_1_at_risk.csv


  get_counts:
    run: python:latest python analysis/scripts/combine_operators.py
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        counts: output/*_count.csv

  generate_top_5_tables:
    run: python:latest python analysis/scripts/top_codes.py
    needs: [get_counts]
    outputs:
      moderately_sensitive:
        counts: output/top_5_code_table_*.csv

  generate_study_population_check_SC:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_check_SC
      --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_check_SC.csv.gz

  generate_measures:
    run: cohortextractor:latest generate_measures 
      --study-definition study_definition
      --output-dir=output/joined
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        measure_csv: output/joined/measure_*_rate.csv
        
  

  generate_plots:
    run: python:latest python analysis/scripts/plot_measures.py
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        counts: output/figures/plot_*.jpeg

  generate_plots_numeric_values:
    run: python:latest python analysis/scripts/plot_numeric_values.py
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        figures: output/*dis*.jpeg

  generate_upset_plots:
    run: python:latest python analysis/scripts/ckd_discrepancies.py
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        figures: output/ckd_staging_upset_*.png
        time: output/time_diff_ckd.jpeg

  # generate_notebook:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/report.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_plots, get_counts]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/report.html

  generate_ukrr_checks:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/ukrr-checks.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [generate_study_population, generate_study_population_ukrr_ethnicity]
    outputs:
      moderately_sensitive:
        report: output/notebooks/ukrr-checks.html

  generate_ukrr_report:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/ukrr-report.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        report: output/notebooks/ukrr-report.html
       
  generate_ukrr_discrepancies:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/ukrr-discrepancies.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        report: output/notebooks/ukrr-discrepancies.html
  
  # generate_kidney_week:
  #   run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/kidney_week.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
  #   needs: [join_cohorts]
  #   outputs:
  #     moderately_sensitive:
  #       report: output/notebooks/kidney_week.html
  
  generate_ukrr_tables_figures:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/ukrr-tables-figures.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [join_cohorts]
    outputs:
      moderately_sensitive:
        report: output/notebooks/ukrr-tables-figures.html

  generate_ukrr_tables_figures_paeds:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/ukrr-tables-figures-paeds.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [generate_study_population_paeds]
    outputs:
      moderately_sensitive:
        report: output/notebooks/ukrr-tables-figures-paeds.html
  
  generate_check_SC:
    run: r:latest -e 'rmarkdown::render("analysis/ukrr-analysis/check-SC.Rmd", knit_root_dir = "/workspace", output_dir = "output/notebooks")'
    needs: [generate_study_population_check_SC, generate_study_population_ukrr_ethnicity]
    outputs:
      moderately_sensitive:
        report: output/notebooks/check-SC.html
  
 # generate_frequency_plots:
 #   run: r:latest analysis/test_frequency.R
 #   needs: [join_cohorts_ethnicity]
 #   outputs:
 #     moderately_sensitive:
 #       figures: output/figures/months_with_*.png

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:47:11

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Succeeded
Backend
TPP
Workspace
renal-short-data-report
Requested by
Shalini Santhakumaran
Branch
main
Force run dependencies
No
Git commit hash
e158f7d
Requested actions
  • generate_check_SC

Code comparison

Compare the code used in this Job Request