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Job request: 11542

Organisation:
ONS
Workspace:
covid_mental_health
ID:
ikawcrbvayg2tqaz
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Luke Lorenzi 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 
# describes how each step in your analysis should be run

version: '3.0'

expectations:
  population_size: 200

actions:

    combine_codelists:
        run: r:latest analysis/combine_codelists.R
        outputs:
            highly_sensitive:
                cmd: 'codelists/ons-cmd-codes.csv'
                smi: 'codelists/ons-smi-codes.csv'
                self_harm : 'codelists/ons-self-harm-codes.csv'
                
    generate_cis_visit_level:
        run: cohortextractor:latest generate_cohort --study-definition study_definition_cis_wide --with-end-date-fix
        needs: [combine_codelists]
        outputs:
            highly_sensitive:
                cohort: output/input_cis_wide.csv
    
    # generate_cmd_counts:
    #     run: cohortextractor:latest generate_cohort --study-definition study_definition_cmd --with-end-date-fix
    #     needs: [combine_codelists]
    #     outputs:
    #         highly_sensitive:
    #             cohort: output/input_cmd.csv
    
    # population_cmd:
    #     run: r:latest analysis/population_cmd.R
    #     needs: [generate_cmd_counts]
    #     outputs:
    #         highly_sensitive:
    #             cohort: output/population_cmd.csv
    
    transform_cis_wide_to_long:
        run: r:latest analysis/cis_wide_to_long.R
        needs: [generate_cis_visit_level]
        outputs:
            highly_sensitive:
                cohort: output/input_cis_long.csv
    
    reconcile_snomed_ctv3:
        run: r:latest analysis/reconcile_snomed_ctv3.R
        needs: [transform_cis_wide_to_long]
        outputs:
            highly_sensitive:
                cohort: output/input_reconciled.csv
    
    derive_exposed:
        run: r:latest analysis/exposed_population.R
        needs: [reconcile_snomed_ctv3]
        outputs:
            highly_sensitive:
                cohort: output/cis_exposed.csv
    
    derive_controls:
        run: r:latest analysis/control_population.R
        needs: [reconcile_snomed_ctv3]
        outputs:
            highly_sensitive:
                cohort: output/cis_control.csv
                
    perform_matching:
        run: r:latest analysis/create_controls.R
        needs: [derive_exposed, derive_controls]
        outputs:
            highly_sensitive:
                incidence: output/incidence_group.csv
                prevalence: output/prevalence_group.csv
                exacerbated: output/exacerbated_group.csv
    
    adjust_matched_groups:
        run: r:latest analysis/adjust_groups.R
        needs: [perform_matching]
        outputs:
            highly_sensitive:
                incidence: output/adjusted_incidence_group.csv
                prevalence: output/adjusted_prevalence_group.csv
    
    descriptive_stats:
        run: r:latest analysis/descriptive_statistics.R
        needs: [adjust_matched_groups]
        outputs:
            moderately_sensitive:
                incidence_cat_stats: output/incidence_cat_stats.csv
                incidence_con_stats: output/incidence_con_stats.csv
                prevalence_cat_stats: output/prevalence_cat_stats.csv
                prevalence_con_stats: output/prevalence_con_stats.csv
    
    cumulative_incidence:
        run: r:latest analysis/cumulative_incidence_curves.R
        needs: [adjust_matched_groups]
        outputs:
            moderately_sensitive:
                inc_ci_cmd: output/incidence_ci_cmd.jpg
                inc_ci_other: output/incidence_ci_other.jpg
                prev_ci_cmd: output/prevalence_ci_cmd.jpg
                prev_ci_other: output/prevalence_ci_other.jpg

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:00:35

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

Job information

Status
Succeeded
Backend
TPP
Workspace
covid_mental_health
Requested by
Luke Lorenzi
Branch
main
Force run dependencies
No
Git commit hash
f48970b
Requested actions
  • cumulative_incidence

Code comparison

Compare the code used in this Job Request