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Job request: 5381

Organisation:
University of Manchester
Workspace:
service_eval_work
ID:
n2lvjnr5x55u6e3e
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Billy Zhong 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: 1000

actions:

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to today by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/measures/input_*.csv.gz
  
  generate_study_population_infection:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_infection --index-date-range "2019-01-01 to today by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/measures/input_infection_*.csv.gz

  generate_study_population_elderly:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_elderly 
      --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/input_elderly.csv.gz

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition --skip-existing --output-dir=output/measures
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measure_*.csv
  
  generate_measures_infection:
    run: cohortextractor:latest generate_measures --study-definition study_definition_infection --skip-existing --output-dir=output/measures
    needs: [generate_study_population_infection]
    outputs:
      moderately_sensitive:
        measure_csv: output/measures/measure_infection_*.csv
        
  # describe_elderly_agedis:
  #   run: r:latest analysis/tables/gen_csv_age_check.R
  #   needs: [generate_study_population_elderly]
  #   outputs:
  #     moderately_sensitive:
  #       agetable: output/age_quant.csv

  # describe:
  #   run: r:latest analysis/plot/overall_ab_prescribing.R
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       cohort: output/overall.png
  #       boxplot: output/overallbox.png

  describe_percentile:
    run: r:latest analysis/plot/overall_ab_prescribing_2575percentile.R
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        percentile: output/overall_25th_75th_percentile.png

  # describe_starpu:
  #   run: r:latest analysis/plot/starpu_ab_prescribing.R
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       cohort: output/starpuline.png
  #       boxplot: output/starpubox.png
  
  # generate_notebook_starpu:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/starpu.ipynb --execute --to html --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/starpu.html 
  #       figures: output/*
  #       #tables: output/tables/*
  #       #csvs: output/*/* # two possible subfolders
  #       #text: output/text/*
  
  describe_service_eval_baseline_table:
    run: r:latest analysis/tables/baseline_table.R
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        baseline_overall: output/overall_counts_blt.csv
        baseline_table: output/blt_one_random_obs_perpat.csv

  # describe_consultation_rate:
  #   run: r:latest analysis/plot/incident_consultation_age_stacked_barchart.R
  #   needs: [generate_measures]
  #   outputs:
  #      moderately_sensitive:
  #       bar1: output/consult_age_UTI.png
  #       bar2: output/consult_age_LRTI.png
  #       bar3: output/consult_age_URTI.png
  #       bar4: output/consult_age_sinusitis.png
  #       bar5: output/consult_age_ot_externa.png
  #       bar6: output/consult_age_otmedia.png
  #       bar7: output/consult_age_repeatedUTI.png
       


  # describe_consultation_prescribed:
  #   run: r:latest analysis/plot/consultation_prescibed_percentage.R
  #   needs: [generate_study_population]
  #   outputs:
  #      moderately_sensitive:
  #       bar1: output/prescribed_percentage_UTI.png
  #       csvs: output/uti_prescrib_check.csv
     

  #generate_notebook_starpu:
  #  run: jupyter:latest jupyter nbconvert /workspace/analysis/starpu.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #  needs: [generate_measures]
  #  outputs:
  #    moderately_sensitive:
  #      notebook: output/hospitalisation_risk/starpu.html 
  #      figures: output/hospitalisation_risk/*
        #tables: output/tables/*
        #csvs: output/*/* # two possible subfolders
        #text: output/text/*

  # generate_notebook_hospitalisation_analysis:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_analysis.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population]
  #   outputs:
  #   moderately_sensitive:
  #       notebook: output/hospitalisation_risk/hospitalisation_analysis.html 
  #       figures: output/hospitalisation_risk/*
    
  # generate_notebook_hospitalisation_analysis:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_analysis.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_risk/hospitalisation_analysis.html 
  #       figures: output/hospitalisation_risk/*

  describe_prior_ab_12mb4:
    run: r:latest analysis/plot/ab_1yb4_stackedbar_2.R
    needs: [generate_study_population]
    outputs:
       moderately_sensitive:
        plot: output/AB_1yb4_line.jpeg
        plot_sex: output/AB_1yb4_SEX.jpeg
        #count_table: output/prior_ab_by_month.csv      


  describe_consultation_rate_all:
    run: r:latest analysis/plot/incident_consultation_by_age_infection.R
    needs: [generate_measures_infection]
    outputs:
       moderately_sensitive:
        plot1: output/consult_age_1.jpeg
        plot2: output/consult_age_2.jpeg
        plot3: output/consult_all.jpeg
        csv1: output/consultation_rate.csv
        csv2: output/consultation_GP_rate.csv

  describe_infection_prescribed_percent:
    run: r:latest analysis/plot/infection_prescibed_percent.R
    needs: [generate_measures_infection]
    outputs:
       moderately_sensitive:
        plot1: output/infection_ab_precent_p1.jpeg
        plot2: output/infection_ab_precent_p2.jpeg
        plot3: output/infection_ab_precent_i1.jpeg
        plot4: output/infection_ab_precent_i2.jpeg
        plot5: output/infection_ab_precent_all.jpeg
        csv1: output/prescribed_infection_prevalent.csv
        csv2: output/prescribed_infection_incident.csv

  describe_top10ABtypes_byInfection:
    run: r:latest analysis/plot/abtypes_top10.R
    needs: [generate_measures_infection]
    outputs:
       moderately_sensitive:
        plot1: output/abtype_UTI.jpeg
        plot2: output/abtype_URTI.jpeg
        plot3: output/abtype_LRTI.jpeg
        plot4: output/abtype_sinusitis.jpeg
        plot5: output/abtype_ot_externa.jpeg
        plot6: output/abtype_otmedia.jpeg
        plot7: output/abtype_percent_UTI.jpeg
        plot8: output/abtype_percent_URTI.jpeg
        plot9: output/abtype_percent_LRTI.jpeg
        plot10: output/abtype_percent_sinusitis.jpeg
        plot11: output/abtype_percent_ot_externa.jpeg
        plot12: output/abtype_percent_otmedia.jpeg
        csv: output/abtype_top10_by_infection.csv
  
  # describe_top10ABtypes_total:
  #   run: r:latest analysis/plot/types_ab_prescriptions.R
  #   needs: [generate_study_population]
  #   outputs:
  #      moderately_sensitive:
  #       plot1: output/abtype_all_Rx.jpeg
  #       plot2: output/abtype_all_Rx_percent.jpeg

  describe_broad_proportion:
    run: r:latest analysis/plot/broad_proportion.R
    needs: [generate_measures]
    outputs:
       moderately_sensitive:
        plot1: output/broad_proportions_line_age.jpeg
        plot2: output/broad_proportions_line.jpeg
        csv1: output/broad_prescriptions_proportion.csv

  describe_same_day_ab_sgss:
    run: r:latest analysis/plot/same_day_covid_ab_sgss.R
    needs: [generate_measures]
    outputs:
       moderately_sensitive:
        plot1: output/same_day_ab_prop_line_sgss_age.jpeg
        plot2: output/same_day_ab_prop_line_sgss.jpeg
        csv1: output/same_day_ab_prop_sgss.csv

  describe_same_day_ab_gp:
    run: r:latest analysis/plot/same_day_covid_ab_gp.R
    needs: [generate_measures]
    outputs:
       moderately_sensitive:
        plot1: output/same_day_ab_prop_line_gp_age.jpeg
        plot2: output/same_day_ab_prop_line_gp.jpeg
        csv1: output/same_day_ab_prop_gp.csv

  generate_study_population_antibiotics: #  Antibiotics_recorded_01
    run: cohortextractor:latest generate_cohort --study-definition study_definition_antibiotics --index-date-range "2019-01-01 to today" --skip-existing --output-dir=output/measures --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/measures/input_antibiotics_*.csv.gz

  describe_ab_recoded_indication_process: #  Antibiotics_recorded_02: generate prescription-level dataset
    run: r:latest analysis/process/ab_recorded_indication_transform.R
    needs: [generate_study_population_antibiotics]
    outputs:
       highly_sensitive:
        rds1: output/measures/recorded_ab_2019.rds
        rds2: output/measures/recorded_ab_2020.rds
        rds3: output/measures/recorded_ab_2021.rds
        rds4: output/measures/recorded_ab_2022.rds

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:05:10

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

Job information

Status
Failed
Backend
TPP
Workspace
service_eval_work
Requested by
Billy Zhong
Branch
main
Force run dependencies
No
Git commit hash
ed2449d
Requested actions
  • describe_same_day_ab_sgss
  • describe_same_day_ab_gp

Code comparison

Compare the code used in this Job Request