Skip to content

Job request: 3500

Organisation:
Bennett Institute
Workspace:
factors-associated-with-covid-19-vaccination
ID:
7hh6unq7ytvhsqe7
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Millie Green 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:
    data_summaries
    Status:
    Status: Failed
    Job identifier:
    aoeyrehbodwdmm2j

Pipeline

Show project.yaml 
######################################

# This script defines the project pipeline - it specifys the execution orders for all the code in this
# repo using a series of actions.

######################################

version: '3.0'

expectations:
  population_size: 1000000

actions:

  # Extract data for study population flow chart
  generate_study_population_flow_chart_data:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_flow_chart
    outputs:
      highly_sensitive:
        cohort: output/input_flow_chart.csv

  # Calculate numbers for study population flow chart
  flow_chart:
    run: r:latest -e 'rmarkdown::render("analysis/R/Markdown/Study_definition_flow_chart.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output/flow_chart")'
    needs: [generate_study_population_flow_chart_data]
    outputs:
      moderately_sensitive:
        html: output/flow_chart/Study_definition_flow_chart.html
        
  # Extract study data
  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition
    outputs:
      highly_sensitive:
        cohort: output/input.csv
        
  # Process data
  data_process:
    run: r:latest analysis/R/Scripts/00_process_data.R
    needs: [generate_study_population]
    outputs:
      highly_sensitive:
        data1: output/data/data_all.rds
        data2: output/data/data_modelling.rds
        
  # Summarise data
  data_properties:
    run: r:latest analysis/R/Scripts/01_data_properties.R output/data/data_all.rds output/data_properties
    needs: [generate_study_population, data_process]
    outputs:
      moderately_sensitive:
        datasummary: output/data_properties/data_all*.txt
        
  # More data summaries
  data_summaries:
    run: r:latest -e 'rmarkdown::render("analysis/R/Markdown/Data_summaries.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        html: output/Data_summaries.html

  # # Coxph models
  # cox_models:
  #   run: r:latest analysis/R/Scripts/02a_models_coxph.R
  #   needs: [generate_study_population, data_process]
  #   outputs:
  #     highly_sensitive :
  #       models: output/models/testing/mod*.rds
        
  # # Coxme model
  # coxme_model:
  #   run: r:latest analysis/R/Scripts/02b_models_coxme.R
  #   needs: [generate_study_population, data_process]
  #   outputs:
  #     highly_sensitive :
  #       models: output/models/testing/mod_test*.rds
  
  # # Model summaries
  # cox_models_summaries:
  #   run: r:latest -e 'rmarkdown::render("analysis/R/Markdown/Model_comparisons.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
  #   needs: [generate_study_population, data_process, cox_models, coxme_model]
  #   outputs:
  #     moderately_sensitive:
  #       html: output/Model_comparisons.html
  
  # # AFT vs Cox models feasibility
  # aft_vs_cox_poc:
  #   run: r:latest analysis/R/Scripts/02c_models_cox_vs_aft_poc.R
  #   needs: [generate_study_population, data_process]
  #   outputs:
  #     highly_sensitive :
  #       models: output/models/testing/cox_vs_aft/mod*.rds
  #     moderately_sensitive:
  #       tables: output/models/testing/cox_vs_aft/table*.csv
  #       plots: output/models/testing/cox_vs_aft/plot*.svg

  # # AFT models
  # aft_vs_cox_models:
  #   run: r:latest analysis/R/Scripts/02d_models_cox_vs_aft.R
  #   needs: [generate_study_population, data_process]
  #   outputs:
  #     highly_sensitive :
  #       models: output/models/cox_vs_aft/mod*.rds
        
  # # Model comparison
  # aft_vs_cox_comparison:
  #   run: r:latest -e 'rmarkdown::render("analysis/R/Markdown/Cox_vs_aft_model_comparison.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
  #   needs: [generate_study_population, data_process, aft_vs_cox_models]
  #   outputs:
  #     moderately_sensitive:
  #       html: output/Cox_vs_aft_model_comparison.html
        
  # Final (stratified cox) model
  model_final:
    run: r:latest analysis/R/Scripts/03_model_final.R
    needs: [generate_study_population, data_process]
    outputs:
      highly_sensitive :
        models: output/model/mod*.rds
      moderately_sensitive:
        csv: output/model/tidy_*.csv
 
  # Strata summaries
  strata_summary:
    run: r:latest analysis/R/Scripts/04_strata_summary.R
    needs: [data_process, model_final]
    outputs:
      moderately_sensitive:
        plots: output/model/plot_strata*.svg
        csv: output/model/cmlhaz_quantiles.csv
  
  # # Results summary
  # results_summary:
  #   run: r:latest -e 'rmarkdown::render("analysis/R/Markdown/Results_summary.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
  #   needs: [data_process, model_final]
  #   outputs:
  #     moderately_sensitive:
  #       html: output/Results_summary.html
        
  # Table and figure
  table_and_figure:
    run: r:latest analysis/R/Scripts/05_table_and_figure.R
    needs: [generate_study_population, data_process, model_final]
    outputs:
      moderately_sensitive:
        table1: output/model/tab*.csv
        table2: output/model/counts_redacted.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:07

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

Job information

Status
Failed
Backend
TPP
Workspace
factors-associated-with-covid-19-vaccination
Requested by
Millie Green
Branch
master
Force run dependencies
No
Git commit hash
9de8bd3
Requested actions
  • data_summaries

Code comparison

Compare the code used in this Job Request