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Job request: 14530

Organisation:
University of Surrey
Workspace:
adtinjectables
ID:
c6tk7rzxddinuswa
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher AgzLeman 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_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_ethnicity.feather

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
    outputs:
      highly_sensitive:
        cohort: output/input.csv

  generate_ADT_rates_1:    
    run: cohortextractor:latest generate_cohort --study-definition study_definition_rates --index-date-range "2015-01-01 to 2018-12-01 by month" --skip-existing --output-dir=output --output-format=feather
    outputs:      
      highly_sensitive:
        cohort: output/measures/inpu*.feather
  
  generate_ADT_rates_2:    
    run: cohortextractor:latest generate_cohort --study-definition study_definition_rates --index-date-range "2019-01-01 to 2022-12-01 by month" --skip-existing --output-dir=output --output-format=feather
    outputs:      
      highly_sensitive:
        cohort: output/measures/inp*.feather

  join_ethnicity:
    run: python:latest python analysis/join_ethnicity.py
    needs:
      [
        generate_ADT_rates_1,
        generate_ADT_rates_2,
        generate_ethnicity,
      ]
    outputs:
      highly_sensitive:
        cohort: output/measures/in*.feather
  
  generate_measures_ADT:
    run: cohortextractor:latest generate_measures --study-definition study_definition_rates --skip-existing --output-dir=output/measures
    needs: 
      [
        generate_ADT_rates_1,
        generate_ADT_rates_2,
        join_ethnicity,
      ]
    outputs:
      moderately_sensitive:
        measure_csv1: output/measures/measure_ADT_inj*_rate.csv
        measure_csv2: output/measures/measure_ADT_inj1*_rate.csv
        measure_csv3: output/measures/measure_ADT_inj3*_rate.csv
        measure_csv4: output/measures/measure_ADT_inj6*_rate.csv
        measure_csv5: output/measures/measure_ADTinjbyRegion*_rate.csv
        measure_csv6: output/measures/measure_ADTinjbyIMD*_rate.csv
        measure_csv7: output/measures/measure_ADTinjbyEthnicity*_rate.csv
        measure_csv8: output/measures/measure_ADTinjbyAge*_rate.csv
        measure_csv9: output/measures/measure_ADT_oral*_rate.csv
        measure_csv10: output/measures/measure_ADToralbyRegion*_rate.csv
        measure_csv11: output/measures/measure_ADToralbyIMD*_rate.csv
        measure_csv12: output/measures/measure_ADToralbyEthnicity*_rate.csv
        measure_csv13: output/measures/measure_ADToralbyAge*_rate.csv

  describe_trends:
    run: r:latest analysis/Descriptive_trends.R
    needs: 
      [
        generate_measures_ADT,
        generate_study_population
      ]
    outputs:
      moderately_sensitive:
        fig1: output/ADT_inj_rat.png
        fig2: output/ADT_inj1_ra.png
        fig3: output/ADT_inj3_ra.png
        fig4: output/ADT_inj6_ra.png
        fig5: output/ADTinjbyReg.png
        fig6: output/ADTinjbyIMD.png
        fig7: output/ADTinjbyEth.png
        fig8: output/ADTinjbyAge.png
        fig9: output/ADT_oral_ra.png
        fig10: output/ADToralbyRe.png
        fig11: output/ADToralbyIM.png
        fig12: output/ADToralbyEt.png
        fig13: output/ADToralbyAg.png
        csv1: output/ADT_inj_rat_rounded.csv
        csv2: output/ADT_inj1_ra_rounded.csv
        csv3: output/ADT_inj3_ra_rounded.csv
        csv4: output/ADT_inj6_ra_rounded.csv
        csv5: output/ADTinjbyReg_rounded.csv
        csv6: output/ADTinjbyIMD_rounded.csv
        csv7: output/ADTinjbyEth_rounded.csv
        csv8: output/ADTinjbyAge_rounded.csv
        csv9: output/ADT_oral_ra_rounded.csv
        csv10: output/ADToralbyRe_rounded.csv
        csv11: output/ADToralbyIM_rounded.csv
        csv12: output/ADToralbyEt_rounded.csv
        csv13: output/ADToralbyAg_rounded.csv
        csv14: output/Table1.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 02:47:42

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

Job information

Status
Succeeded
Backend
TPP
Workspace
adtinjectables
Requested by
AgzLeman
Branch
main
Force run dependencies
No
Git commit hash
4260bd4
Requested actions
  • generate_study_population
  • describe_trends

Code comparison

Compare the code used in this Job Request