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Job request: 16989

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
openprompt_longcovid_vaccines
ID:
vyod4eszymyb556i
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Alasdair Henderson requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
 population_size: 20000

actions:

  generate_dataset_cases:
    run: >
      databuilder:v0 
        generate-dataset analysis/dataset_definition_cases.py --output output/dataset_cases.csv.gz
    outputs:
      highly_sensitive:
        dataset_cases: output/dataset_cases.csv.gz
  
  generate_dataset_controls:
    run: >
      databuilder:v0 
        generate-dataset analysis/dataset_definition_controls.py --output output/dataset_controls.csv.gz
    outputs:
      highly_sensitive:
        dataset_controls: output/dataset_controls.csv.gz
  
  generate_dataset_lc_pre_vacc:
    run: >
      databuilder:v0 
        generate-dataset analysis/dataset_definition_longcovid_prevaccine.py --output output/dataset_lc_pre_vacc.csv.gz
    outputs:
      highly_sensitive:
        dataset_controls: output/dataset_lc_pre_vacc.csv.gz
  
  clean_the_data: 
    run: > 
      r:latest
        analysis/010_cleandata.R
    needs: [generate_dataset_cases, generate_dataset_controls]
    outputs: 
      highly_sensitive:
        cleandata: output/clean_dataset.gz.parquet 
      moderately_sensitive: 
        txt1: output/data_properties/clean_dataset_skim.txt
        txt2: output/data_properties/clean_dataset_tabulate.txt

  time_update_data: 
    run: >
      r:latest
        analysis/011_timeupdate_data.R
    needs: [clean_the_data]
    outputs: 
      highly_sensitive: 
        timedata_longcovid: output/timeupdate_dataset_lc_all.gz.parquet
        timedata_longcovid_dx: output/timeupdate_dataset_lc_dx.gz.parquet
        timedata_fracture: output/timeupdate_dataset_fracture.gz.parquet
      moderately_sensitive: 
        txt3: output/data_properties/timeupdated_dataset_skim.txt

  summarise_timedata: 
    run: >
      r:latest
        analysis/012_timeupdated_summary.R
    needs: [time_update_data]
    outputs: 
      moderately_sensitive: 
        txt4: output/data_properties/timeupdated_lc_all_tabulate.txt
        lc_all_t_plot: output/supplementary/time_updated_t_byvaccines.pdf
        lc_dx_t_plot: output/supplementary/time_updated_t_byvaccines_lc_dx.pdf

  crude_rates:
    run: >
      r:latest
        analysis/020_cruderates.R
    needs: [clean_the_data]
    outputs:
      moderately_sensitive:
        cruderates: output/tab021_crude_lc_rates.csv

  crude_rates_timeupdated:
    run: >
      r:latest
        analysis/021_cruderates_timeupdated.R
    needs: [time_update_data]
    outputs:
      moderately_sensitive:
        t_cruderates_lc_all: output/tab022_tuv_rates_lc_all.csv
        t_cruderates_lc_dx: output/tab023_tuv_rates_lc_dx.csv

  plot_incidence:
    run: >
      r:latest
        analysis/030_plotrates.R
    needs: [clean_the_data, time_update_data]
    outputs:
      moderately_sensitive:
        cuminc: output/figures/fig1_cumulative_incidence.pdf
        rawcountsplot: output/figures/fig2_raw_counts_line.pdf
        rawcount: output/figures/fig2b_raw_counts_column.pdf
        vaccinegap: output/supplementary/fig_agegap_vaccines.pdf

  poisson_rates_static:
    run: >
      r:latest
        analysis/040_poisson_regressions_staticvars.R
    needs: [clean_the_data]
    outputs:
      moderately_sensitive:
        poissonrates: output/tab023_poissonrates_static.csv

  poisson_rates_timeupdated:
    run: >
      r:latest
        analysis/041_poisson_regressions_timeupdated.R
    needs: [time_update_data]
    outputs:
      moderately_sensitive:
        poissonrates: output/tab023_poissonrates_timeupdated.csv

  poisson_plots:
    run: >
      r:latest
        analysis/042_plot_poisson_results.R
    needs: [poisson_rates_static, poisson_rates_timeupdated]
    outputs: 
      moderately_sensitive: 
        poissonplots_all: output/figures/fig3a_rate_ratios.pdf
        poissonplots_lc: output/figures/fig3b_rate_ratios_longcovid.pdf
        poissonplots_lc_adjusted: output/figures/fig3c_rate_ratios_adjustedonly.pdf
        poissonplots_control: output/figures/fig3d_rate_ratios_controloutcome.pdf

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 14:54:55

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

Job request

Status
Succeeded
Backend
TPP
Workspace
openprompt_longcovid_vaccines
Requested by
Alasdair Henderson
Branch
main
Force run dependencies
No
Git commit hash
5eb0d12
Requested actions
  • generate_dataset_cases
  • generate_dataset_controls
  • generate_dataset_lc_pre_vacc
  • clean_the_data
  • time_update_data
  • summarise_timedata
  • crude_rates
  • crude_rates_timeupdated
  • plot_incidence

Code comparison

Compare the code used in this job request