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Job request: 4918

Organisation:
University of Bristol
Workspace:
covid-ve-change-over-time--combine-jcvi-groups-in-model
ID:
gbf5j2jvfuftmvsu
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
        outcomes: output/lib/outcomes.rds
        subgroups: output/lib/subgroups.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_all: output/data/data_*.rds
      moderately_sensitive:
        data_properties: output/tables/data_*_tabulate.txt

  ## 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/second_vax_period/data/second_vax_period_dates.rds
      moderately_sensitive:
        second_vax_period_dates_txt: output/second_vax_period/tables/second_vax_period_dates.txt

  ## 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, d and e 

  data_eligible_cde:
    run: r:latest analysis/second_vax_period/data_eligible_cde.R
    needs:
    - design
    - data_input_process
    - data_eligible_ab
    - data_2nd_vax_dates
    outputs:
      highly_sensitive:
        data_eligible_e_vax: output/data/data_eligible_e_vax.rds
        data_eligible_e_unvax: output/data/data_eligible_e_unvax.rds

  ## #################################### 
  ## comparisons 
  ## #################################### 
  ## process comparisons data 

  data_comparisons_process:
    run: r:latest analysis/comparisons/data_comparisons_process.R
    needs:
    - design
    - data_input_process
    - data_2nd_vax_dates
    - data_eligible_cde
    outputs:
      highly_sensitive:
        data_comparisons: output/comparisons/data/data_comparisons_*.rds

  ## process tte data 

  data_tte_process_BNT162b2:
    run: r:latest analysis/comparisons/data_tte_process.R BNT162b2
    needs:
    - design
    - data_input_process
    - data_comparisons_process
    outputs:
      highly_sensitive:
        data_tte_brand_outcome: output/tte/data/data_tte_BNT162b2*.rds
        event_counts: output/tte/tables/event_counts_BNT162b2.rds

  data_tte_process_ChAdOx:
    run: r:latest analysis/comparisons/data_tte_process.R ChAdOx
    needs:
    - design
    - data_input_process
    - data_comparisons_process
    outputs:
      highly_sensitive:
        data_tte_brand_outcome: output/tte/data/data_tte_ChAdOx*.rds
        event_counts: output/tte/tables/event_counts_ChAdOx.rds

  data_tte_process_both:
    run: r:latest analysis/comparisons/data_tte_process.R both
    needs:
    - design
    - data_input_process
    - data_comparisons_process
    outputs:
      highly_sensitive:
        data_tte_brand_outcome: output/tte/data/data_tte_both*.rds
        event_counts: output/tte/tables/event_counts_both.rds

  ## process event counts tables 

  process_event_count_tables_BNT162b2:
    run: r:latest analysis/comparisons/process_event_count_tables.R BNT162b2
    needs:
    - design
    - data_tte_process_BNT162b2
    outputs:
      moderately_sensitive:
        tables_events: output/tte/tables/events_BNT162b2*.csv
        tidy_tables_events: output/tte/tables/tidy_events_BNT162b2*.txt

  process_event_count_tables_ChAdOx:
    run: r:latest analysis/comparisons/process_event_count_tables.R ChAdOx
    needs:
    - design
    - data_tte_process_ChAdOx
    outputs:
      moderately_sensitive:
        tables_events: output/tte/tables/events_ChAdOx*.csv
        tidy_tables_events: output/tte/tables/tidy_events_ChAdOx*.txt

  process_event_count_tables_both:
    run: r:latest analysis/comparisons/process_event_count_tables.R both
    needs:
    - design
    - data_tte_process_both
    outputs:
      moderately_sensitive:
        tables_events: output/tte/tables/events_both*.csv
        tidy_tables_events: output/tte/tables/tidy_events_both*.txt

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:53:13

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

Job information

Status
Succeeded
Backend
TPP
Workspace
covid-ve-change-over-time--combine-jcvi-groups-in-model
Requested by
Elsie Horne
Branch
combine-jcvi-groups-in-model
Force run dependencies
No
Git commit hash
f360154
Requested actions
  • data_eligible_ab
  • data_2nd_vax_dates
  • plot_2nd_vax_dates
  • data_eligible_cde
  • data_comparisons_process
  • data_tte_process_BNT162b2
  • data_tte_process_ChAdOx
  • data_tte_process_both
  • process_event_count_tables_BNT162b2
  • process_event_count_tables_ChAdOx
  • process_event_count_tables_both

Code comparison

Compare the code used in this Job Request