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Job request: 10384

Organisation:
The London School of Hygiene & Tropical Medicine
Workspace:
disect_uk_india_covid
ID:
qzoxgqx7la4fff7n
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Rohini Mathur 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_check_w2
    Status:
    Status: Failed
    Job identifier:
    ztco43bndazfi4x7

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_study_population_w1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_w1
    outputs:
      highly_sensitive:
        cohort: output/input_w1.csv


  generate_study_population_w2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_w2
    outputs:
      highly_sensitive:
        cohort: output/input_w2.csv

  
  generate_study_population_w3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_w3
    outputs:
      highly_sensitive:
        cohort: output/input_w3.csv
  

  analyse_w1:
    run: r:latest analysis/analysis_wave1_long.R
    needs: [generate_study_population_w1]
    outputs:
      moderately_sensitive:
        table1a: output/table1a_w1.csv
        table1c: output/table1c_w1.csv
        unadjusted_severe: output/unadjusted_severe_w1.csv
        unadjusted_long: output/unadjusted_long_w1.csv

# Currently wave 2 is correct so only run W2 scripts in jobs runner
  analyse_w2_long:
    run: r:latest analysis/analysis_wave2_long.R
    needs: [generate_study_population_w2]
    outputs:
      moderately_sensitive:
        table1a_long: output/table1a_w2_long.csv
        table1b_long: output/table1b_w2_long.csv
        long_incidence: output/long_incidence_w2.csv
        long_incidence_strata: output/long_incidence_strata_w2.csv
        unadjusted_long: output/unadjusted_long_w2.csv


  analyse_w2_severe:
    run: r:latest analysis/analysis_wave2_severe.R
    needs: [generate_study_population_w2]
    outputs:
      moderately_sensitive:
        table1a: output/table1a_w2.csv
        table1b: output/table1b_w2.csv
        severe_incidence: output/severe_incidence_w2.csv
        severe_incidence_strata: output/severe_incidence_strata_w2.csv
        unadjusted_long: output/unadjusted_severe_w2.csv
  
  data_check_w2:
    run: r:latest analysis/analysis_wave2_checks.R
    needs: [generate_study_population_w2]
    outputs:
      moderately_sensitive:
        sample_size_table: output/sample_size_table_w2.csv
        missing_nums: output/missing_nums_w2.csv
        continuous_checks: output/continuous_checks_w2.csv
        dates_dmy: output/dates_dmy_w2.csv
        dates_my: output/dates_my_w2.csv
        binary_checks: output/binary_checks_w2.csv
        eth_tab: output/ethnicity5_w2.csv
        eth16_tab: output/ethnicity16_w2.csv
        sex_tab: output/sex_w2.csv
        smoke_tab: output/smoke_w2.csv
        imd_tab: output/imd_w2.csv
        stp_tab: output/stp_w2.csv
        region_tab: output/region_w2.csv
        diabetes_tab: output/diabetes_w2.csv
        carehome_tab: output/carehome_w2.csv
        covid_diagnosis_tab: output/covid_diagnosis_w2.csv

  analyse_w3:
    run: r:latest analysis/analysis_wave3_long.R
    needs: [generate_study_population_w3]
    outputs:
      moderately_sensitive:
        table1a: output/table1a_w3.csv
        table1c: output/table1c_w3.csv
        unadjusted_severe: output/unadjusted_severe_w3.csv
        unadjusted_long: output/unadjusted_long_w3.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 01:10:46

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

Job information

Status
Failed
Backend
TPP
Workspace
disect_uk_india_covid
Requested by
Rohini Mathur
Branch
main
Force run dependencies
No
Git commit hash
d3d8083
Requested actions
  • data_check_w2

Code comparison

Compare the code used in this Job Request