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Job request: 4784

Organisation:
University of Bristol
Workspace:
covid-ve-change-over-time--process-data-for-models
ID:
bgswtwflpwp3uk2w
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Elsie Horne 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: 100000

actions:

  ## #################################### 
  ## preliminaries 
  ## #################################### 

  design:
    run: r:latest analysis/design.R
    outputs:
      moderately_sensitive:
        study_dates_json: output/lib/study_parameters.json
        study_dates_rds: output/lib/study_parameters.rds
        jcvi_groups: output/lib/jcvi_groups.csv
        elig_dates: output/lib/elig_dates.csv
        regions: output/lib/regions.csv
        model_varlist: output/lib/model_varlist.rds

  ## #################################### 
  ## vax 
  ## #################################### 
  ## data for eligibility criteria and vaccines 
  ## generate dummy data for study_definition_vax 

  dummy_data_vax:
    run: r:latest analysis/vax/dummy_data_vax.R
    needs:
    - design
    outputs:
      moderately_sensitive:
        dummy_data_vax: analysis/vax/dummy_data_vax.feather

  ## study definition for eligiblity criteria and vaccine data 

  generate_study_population_vax:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_vax
      --output-format feather
    dummy_data_file: analysis/vax/dummy_data_vax.feather
    needs:
    - design
    - dummy_data_vax
    outputs:
      highly_sensitive:
        cohort_vax: output/input_vax.feather

  ## process data from study_definition_vax 

  data_vax_process:
    run: r:latest analysis/vax/data_vax_process.R
    needs:
    - design
    - dummy_data_vax
    - generate_study_population_vax
    outputs:
      highly_sensitive:
        data_vax_covs: output/data/data_vax_covs.rds
        data_vax_dates: output/data/data_*_vax_dates.rds
      moderately_sensitive:
        data_properties: output/vax/tables/data_vax_processed_tabulate.txt

  ## apply eligiblity criteria from boxes a and b 

  data_eligible_ab:
    run: r:latest analysis/vax/data_eligible_ab.R
    needs:
    - design
    - data_vax_process
    outputs:
      highly_sensitive:
        data_eligible_a: output/data/data_eligible_a.rds
        data_eligible_b: output/data/data_eligible_b.rds
      moderately_sensitive:
        eligibility_count: output/lib/eligibility_count_ab.csv
        group_age_ranges: output/lib/group_age_ranges.csv

  ## #################################### 
  ## second_vax_period 
  ## #################################### 
  ## identify second vaccination time periods 
  ## create dataset for identifying second vaccination time periods 

  data_2nd_vax_dates:
    run: r:latest analysis/second_vax_period/data_2nd_vax_dates.R
    needs:
    - design
    - data_vax_process
    - data_eligible_ab
    outputs:
      highly_sensitive:
        data_vax_plot: output/second_vax_period/data/data_vax_plot.rds
        second_vax_period_dates_rds: output/lib/second_vax_period_dates.rds
      moderately_sensitive:
        second_vax_period_dates_csv: output/lib/second_vax_period_dates.csv
        start_dates: output/lib/start_dates.csv
        end_dates: output/lib/end_dates.csv

  ## identify and plot second vaccination time periods 

  plot_2nd_vax_dates:
    run: r:latest analysis/second_vax_period/plot_2nd_vax_dates.R
    needs:
    - design
    - data_eligible_ab
    - data_2nd_vax_dates
    outputs:
      moderately_sensitive:
        plots_by_region: output/second_vax_period/images/plot_by_region_*.png

  ## apply eligiblity criteria from boxes c and d 

  data_eligible_cd:
    run: r:latest analysis/second_vax_period/data_eligible_cd.R
    needs:
    - design
    - data_vax_process
    - data_eligible_ab
    - data_2nd_vax_dates
    outputs:
      highly_sensitive:
        data_eligible_c: output/data/data_eligible_c.rds
        data_eligible_d: output/data/data_eligible_d.rds

  ## #################################### 
  ## covs 
  ## #################################### 
  ## data for covariates 
  ## generate dummy data for study_definition_covs 

  dummy_data_covs:
    run: r:latest analysis/covs/dummy_data_covs.R
    needs:
    - design
    - dummy_data_vax
    - data_2nd_vax_dates
    outputs:
      moderately_sensitive:
        dummy_data_vax: analysis/covs/dummy_data_covs.feather

  ## study definition for covariates 

  generate_study_population_covs:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_covs
      --output-format feather
    dummy_data_file: analysis/covs/dummy_data_covs.feather
    needs:
    - design
    - data_2nd_vax_dates
    - dummy_data_covs
    outputs:
      highly_sensitive:
        cohort_vax: output/input_covs.feather

  # ## process recurring variables as long data 

  # data_long_process:
  #   run: r:latest analysis/covs/data_long_process.R
  #   needs:
  #   - design
  #   - data_eligible_cd
  #   - generate_study_population_covs
  #   outputs:
  #     highly_sensitive:
  #       data_long_dates: output/data/data_long_*_dates.rds

  # ## #################################### 
  # ## comparisons 
  # ## #################################### 
  # ## process data, apply model and generate report for JCVI group 02 
  # ## process covariates data 

  # data_comparisons_process_02:
  #   run: r:latest analysis/comparisons/data_comparisons_process.R 02
  #   needs:
  #   - design
  #   - data_vax_process
  #   - data_2nd_vax_dates
  #   - data_eligible_cd
  #   - generate_study_population_covs
  #   - data_long_process
  #   outputs:
  #     highly_sensitive:
  #       data_comparisons: output/jcvi_group_02/data/data_comparisons.rds

  # ## process outcomes data 

  # data_outcomes_process_02:
  #   run: r:latest analysis/comparisons/data_outcomes_process.R 02
  #   needs:
  #   - design
  #   - generate_study_population_covs
  #   - data_long_process
  #   - data_comparisons_process_02
  #   outputs:
  #     highly_sensitive:
  #       data_outcomes: output/jcvi_group_02/data/data_outcomes.rds

  # ## check gap between outcomes for combining 

  # check_combine_outcomes_02:
  #   run: r:latest analysis/comparisons/check_combine_outcomes.R 02
  #   needs:
  #   - data_outcomes_process_02
  #   outputs:
  #     highly_sensitive:
  #       data_check_combine_outcomes: output/jcvi_group_02/data/check_combine_outcomes.rds
  #     moderately_sensitive:
  #       plot_check_combine_outcomes: output/jcvi_group_02/images/check_combine_outcomes.png
  #       table_check_combine_outcomes: output/jcvi_group_02/tables/check_combine_outcomes.csv

  # ## outcome = postest 
  # ## process tte data for postest 

  # data_tte_process_02_postest:
  #   run: r:latest analysis/comparisons/data_tte_process.R 02 postest
  #   needs:
  #   - data_comparisons_process_02
  #   - data_outcomes_process_02
  #   outputs:
  #     highly_sensitive:
  #       data_tte_brand_outcome: output/jcvi_group_02/data/data_tte_*_postest.rds

  # ## apply cox model for postest 

  # apply_model_cox_02_postest:
  #   run: r:latest analysis/comparisons/apply_model_cox.R 02 postest
  #   needs:
  #   - design
  #   - data_comparisons_process_02
  #   - data_tte_process_02_postest
  #   outputs:
  #     highly_sensitive:
  #       modelnumber: output/jcvi_group_02/models/*_postest_model*.rds
  #       model_tidy_rds: output/jcvi_group_02/models/*_postest_modelcox_tidy.rds
  #     moderately_sensitive:
  #       model_glance: output/jcvi_group_02/models/*_postest_modelcox_glance.csv
  #       model_tidy_csv: output/jcvi_group_02/models/*_postest_modelcox_tidy.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:24:24

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

Job information

Status
Failed
Backend
TPP
Workspace
covid-ve-change-over-time--process-data-for-models
Requested by
Elsie Horne
Branch
process-data-for-models
Force run dependencies
No
Git commit hash
5597cb3
Requested actions
  • dummy_data_covs
  • generate_study_population_covs

Code comparison

Compare the code used in this Job Request