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Job request: 4787

Organisation:
University of Bristol
Workspace:
covid-ve-change-over-time--process-data-for-models
ID:
ydjerqpdymy7lhvk
View repo View project.yaml

This page shows the technical details of what happened when 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 indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; 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

  ## #################################### 
  ## study definition 
  ## #################################### 
  ## generate dummy data for study_definition 

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

  ## study definition 

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
      --output-format feather
    dummy_data_file: analysis/dummy_data.feather
    needs:
    - design
    - dummy_data
    outputs:
      highly_sensitive:
        cohort: output/input.feather

  ## #################################### 
  ## preprocessing 
  ## #################################### 
  ## process data from study_definition 

  data_input_process:
    run: r:latest analysis/preprocess/data_input_process.R
    needs:
    - design
    - dummy_data
    - generate_study_population
    outputs:
      highly_sensitive:
        data_covs: output/data/data_covs.rds
        data_vax_dates: output/data/data_*_vax_dates.rds
      moderately_sensitive:
        data_properties: output/tables/data_processed_tabulate.txt

  ## process recurring variables as long data 

  data_long_process:
    run: r:latest analysis/preprocess/data_long_process.R
    needs:
    - design
    - data_input_process
    outputs:
      highly_sensitive:
        data_long_dates: output/data/data_long_*_dates.rds

  ## apply eligiblity criteria from boxes a and b 

  data_eligible_ab:
    run: r:latest analysis/preprocess/data_eligible_ab.R
    needs:
    - design
    - data_input_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_input_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

  ## 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_input_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

  ## #################################### 
  ## 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_input_process
    - data_long_process
    - data_2nd_vax_dates
    - data_eligible_cd
    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
    - data_input_process
    - 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: 05:16:11

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
Yes
Git commit hash
c145931
Requested actions
  • run_all

Code comparison

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