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Job request: 18804

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
openprompt_longcovid_vaccines
ID:
q2yo3vaqpd3nok72
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/raw_dataset_skim.txt
        txt2: output/data_properties/raw_dataset_tabulate.txt
        txt3: output/data_properties/clean_dataset_skim.txt
        txt4: output/data_properties/clean_dataset_tabulate.txt

  clean_lc_pre_vacc_data: 
    run: >
      r:latest
        analysis/0101_clean_lcfirst_cohort.R
    needs: [generate_dataset_lc_pre_vacc]
    outputs: 
      highly_sensitive: 
        cleandata_lcfirst: output/clean_dataset_lc_first.gz.parquet
      moderately_sensitive: 
        txt5: output/data_properties/lcfirst_cohort_skim.txt
        txt6: output/data_properties/lcfirst_cohort_tabulate.txt
        tab1_lc_first: output/tables/tab1_full_description_lc_first.html
  
  plot_vaccine_after_longcovid: 
    run: >
      r:latest
        analysis/0102_vaccine_after_longcovid.R
    needs: [clean_lc_pre_vacc_data, clean_the_data]
    outputs: 
      moderately_sensitive: 
        vaccine_pct_plot: output/figures/fig6_vaccine_after_lc.pdf
        vaccine_pct_data: output/lc_first_vaccination.csv

  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
        timedata_covidhosp: output/timeupdate_dataset_covidhosp.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
  
  summarise_cohort_at_baseline: 
    run: >
      r:latest
        analysis/013_create_table1.R
    needs: [clean_the_data]
    outputs: 
      moderately_sensitive: 
        table1: output/tables/tab1_baseline_description.html
        table1_csv: output/tab1_baseline_data.csv
        table2: output/tables/tab2_fup_description.html
        table2_csv: output/tab2_fup_data.csv
        vaccine_lc_gap: output/supplementary/fig_vaccines_longcovid_gap.pdf
        vaccine_lc_gap_detail: output/supplementary/fig_vaccines_longcovid_gap_zoomed.pdf
        vaccine_lc_gap_csv: output/supplementary/vaccines_longcovid_gap.csv
        

  calculate_monthly_dynamics: 
    run: > 
      r:latest
        analysis/014_calculate_monthly_dynamics.R
    needs: [clean_the_data]
    outputs: 
      moderately_sensitive: 
        monthly_dynamics: output/data_monthly_dynamics.csv
        table_monthly_dynamics: output/tables/supptab01_monthly_dynamics.csv
  
  calculate_daily_dynamics: 
    run: > 
      r:latest
        analysis/015_calculate_daily_dynamics.R
    needs: [clean_the_data]
    outputs: 
      moderately_sensitive: 
        daily_dynamics: output/data_daily_dynamics.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
  
  output_crude_rates:
    run: >
      r:latest
        analysis/022_combine_cruderates.R
    needs: [crude_rates_timeupdated]
    outputs:
      moderately_sensitive:
        cruderates_redacted: output/tables/tab3_crude_rates_redacted.csv
        cruderates_plot: output/figures/fig3_crude_rates.pdf
  
  plot_incidence:
    run: >
      r:latest
        analysis/030_plotrates.R
    needs: [time_update_data]
    outputs:
      moderately_sensitive:
        counts_line: output/figures/fig2_raw_counts_line.pdf
        counts_line_sex: output/figures/fig2a_raw_counts_line_bysex.pdf
        countscolumn: output/figures/fig2b_raw_counts_column.pdf
        countscolumn_sex: output/figures/fig2c_raw_counts_column_bysex.pdf
        stackedbar: output/figures/fig2e_longcovid_stacked_dx_rx.pdf
        multipanelfig: output/figures/fig2_longcovid_dynamics.pdf
        vaccinegap: output/supplementary/fig_agegap_vaccines.pdf

  longcovid_by_snomedcode:
    run: >
      r:latest
        analysis/031_longcovid_by_snomedcode.R
    needs: [clean_the_data]
    outputs:
      moderately_sensitive:
        tab_snomedcode_count: output/tables/tab5_snomedcode_count.csv
        fig_snomedcode_over_time: output/figures/fig2f_raw_counts_by_code.pdf
        tab_snomedcode_over_time: output/raw_counts_by_code_over_time.csv

  plot_longcovid_flows:
    run: >
      r:latest
        analysis/032_pathways_to_longcovid.R
    needs: [clean_the_data]
    outputs:
      moderately_sensitive:
        tests_lc_table: output/tables/tab_tests_and_longcovid.html
        tests_density: output/supplementary/test_to_longcovid_density.pdf
        longcovid_flows: output/figures/fig5_longcovid_flows.pdf
        longcovid_flows_data: output/sankey_plot_data.csv
        demographics_by_test_status: output/tables/tab_demographics_by_test_status.html
        demographics_by_test_status_csv: output/data_demographics_by_test_status.csv
        demographics_by_dx_rx_tbl: output/tables/tab_demographics_by_dx_rx.html
        demographics_by_dx_rx_csv: output/data_demographics_by_dx_rx.csv
  
  plot_daily_dynamics:
    run: >
      r:latest
        analysis/033_plot_daily_dynamics.R
    needs: [calculate_daily_dynamics]
    outputs:
      moderately_sensitive:
        dailydynamics_plot: output/figures/fig4f_daily_cases.pdf
        dailydynamics_data: output/data_daily_dynamics_plot.csv
  
  plot_monthly_dynamics:
    run: >
      r:latest
        analysis/034_plot_monthly_dynamics.R
    needs: [calculate_monthly_dynamics]
    outputs:
      moderately_sensitive:
        monthly_plot_v1: output/figures/fig4a_outbreak_dynamics.pdf
        monthly_plot_v2: output/figures/fig4b_outbreak_dynamics_cumulative.pdf
        monthly_plot_v3: output/figures/fig4c_outbreak_dynamics_experimental.pdf
        monthly_plot_v4: output/figures/fig4d_outbreak_dynamics_log.pdf
        monthly_plot_v5: output/figures/fig4e_longcovid_and_national_cases.pdf

  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_timeupdated]
    outputs: 
      moderately_sensitive: 
        #fig3a: output/figures/fig3a_crude_RRs.pdf
        fig3b: output/figures/fig3b_adjusted_RRs.pdf
        #fig3c: output/figures/fig3c_longcovid_RRs.pdf
        #fig3d: output/figures/fig3d_longcovid_models.pdf
        fig3e: output/figures/fig3e_vaccines.pdf
        #fig3f: output/figures/fig3f_longcovid_vaccine_models.pdf
        #fig3g: output/figures/fig3g_demographics.pdf
        #poissonplots_all: output/figures/fig3h_rate_ratios_facet.pdf
        poissonplots_table: output/tables/tab4_poisson_rateratios.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:02:50

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
7949080
Requested actions
  • plot_vaccine_after_longcovid

Code comparison

Compare the code used in this job request