Job request: 4783

Organisation:: University of Bristol
Workspace:: covid-ve-change-over-time--process-data-for-models
ID:: kwabzieu76b34gc5

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

Action:

design

Status:

Status: Succeeded

Job identifier:

3pumwk6r5ei6h2vt
Action:

dummy_data_covs

Status:

Status: Succeeded

Job identifier:

x4lkoeox5fq47pea
Action:

generate_study_population_covs

Status:

Status: Failed

Job identifier:

xc46eksrgcisejxe
Action:

apply_model_cox_02_postest

Status:

Status: Failed

Job identifier:

7thcjg2rapvdkdvp
Action:

check_combine_outcomes_02

Status:

Status: Failed

Job identifier:

5jnyr6nbpjekskny
Action:

data_tte_process_02_postest

Status:

Status: Failed

Job identifier:

f3qma77bnsrcb7wk
Action:

data_outcomes_process_02

Status:

Status: Failed

Job identifier:

6nnb2vkyqjccu5ue
Action:

data_comparisons_process_02

Status:

Status: Failed

Job identifier:

qzo5a63qfxektwmz
Action:

data_long_process

Status:

Status: Failed

Job identifier:

4g4njub2yfhq7cpd

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: 3 years ago 21 Dec 2021 18:38:45 UTC
Started: 3 years ago 21 Dec 2021 18:38:59 UTC
Finished: 3 years ago 21 Dec 2021 18:55:09 UTC
Runtime: 00:15:34

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: 8abe390
Requested actions: design

dummy_data_covs

generate_study_population_covs

data_long_process

data_comparisons_process_02

data_outcomes_process_02

check_combine_outcomes_02

data_tte_process_02_postest

apply_model_cox_02_postest

Code comparison

Compare the code used in this Job Request