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Job request: 17748

Organisation:
ONS
Workspace:
covid_mental_health
ID:
daquizvtakjaury3
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Klaudia Rzepnicka 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: 1000

actions:
                
    generate_wide_non_health:
        run: cohortextractor:latest generate_cohort --study-definition study_definition_non_health --with-end-date-fix
        outputs:
            highly_sensitive:
                cohort: output/input_non_health.csv
    
    generate_wide_health_mh:
        run: cohortextractor:latest generate_cohort --study-definition study_definition_health_mh --with-end-date-fix
        outputs:
            highly_sensitive:
                cohort: output/input_health_mh.csv
                
    generate_wide_health_non_mh:
        run: cohortextractor:latest generate_cohort --study-definition study_definition_health_non_mh --with-end-date-fix
        outputs:
            highly_sensitive:
                cohort: output/input_health_non_mh.csv

    generate_wide_ons_cis_new:
        run: >
            databuilder:v0
                generate-dataset
                --output output/dataset_ons_cis_new.csv
                analysis/dataset_definition_ons_cis_new.py
        outputs:
            highly_sensitive:
                dataset: output/dataset_ons_cis_new.csv


    combine_wide_data:
        run: r:latest analysis/1_combine_wide_data.R
        needs: [generate_wide_non_health, generate_wide_health_mh, generate_wide_health_non_mh, generate_wide_ons_cis_new]
        outputs:
            highly_sensitive:
                cohort: output/input_cis_wide.csv
        
    transform_cis_wide_to_long:
        run: r:latest analysis/2_cis_wide_to_long.R
        needs: [combine_wide_data]
        outputs:
            highly_sensitive:
                cohort: output/input_cis_long.csv
    
    reconcile_snomed_ctv3:
        run: r:latest analysis/3_reconcile_snomed_ctv3.R
        needs: [transform_cis_wide_to_long]
        outputs:
            highly_sensitive:
                cohort: output/input_reconciled.csv
                #bmi: output/bmi_summary_table_info_before_cap.csv
    
    derive_exposed:
        run: r:latest analysis/4_exposed_population.R
        needs: [reconcile_snomed_ctv3]
        outputs:
            highly_sensitive:
                cohort: output/cis_exposed.csv
    
    derive_controls:
        run: r:latest analysis/5_control_population.R
        needs: [reconcile_snomed_ctv3]
        outputs:
            highly_sensitive:
                cohort: output/cis_control.csv
                
    perform_matching:
        run: r:latest analysis/6_create_controls.R
        needs: [derive_exposed, derive_controls]
        outputs:
            highly_sensitive:
                incidence: output/incidence_group.csv
                prevalence: output/prevalence_group.csv

    testing_exposed_post_pre_matching:
        run: r:latest analysis/6_6_pre_post_match_testing.R
        needs: [derive_exposed, derive_controls,perform_matching]
        outputs: 
            moderately_sensitive:
                t1: output/matching_rates_incidence.csv
                t2: output/matching_rates_prevalence.csv

    adjust_matched_groups:
        run: r:latest analysis/7_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/8_descriptive_statistics.R
        needs: [adjust_matched_groups]
        outputs:
            moderately_sensitive:
                incidence_cat_stats: output/1_descriptives_incidence_cat.csv
                incidence_con_stats: output/2_descriptives_incidence_con.csv
                prevalence_cat_stats: output/3_descriptives_prevalence_cat.csv
                prevalence_con_stats: output/4_descriptives_prevalence_con.csv
    
    cumulative_incidence:
        run: r:latest analysis/9_cumulative_incidence_curves.R
        needs: [adjust_matched_groups]
        outputs:
            highly_sensitive:
                inc_t: output/incidence_t.csv
                prev_t: output/prevalence_t.csv
            moderately_sensitive:
                inc_surv: output/incidence_surv.jpg
                prev_surv: output/prevalence_surv.jpg
                
    hazard_ratios:
        run: r:latest analysis/10_new_hazard_ratio_code.R
        needs: [cumulative_incidence]
        outputs:
            moderately_sensitive:
                temp: output/5_cox_hazard_ratio_incidence_table.csv
                temp2: output/6_cox_hazard_ratio_prevalence_table.csv
                surv1: output/1_survfit_plot_incidence_noadj.jpg
                surv2: output/2_survfit_plot_prevalence_noadj.jpg
                surv3: output/3_survfit_plot_incidence_min.jpg
                surv4: output/4_survfit_plot_prevalence_min.jpg
                surv5: output/5_survfit_plot_incidence_full.jpg
                surv6: output/6_survfit_plot_prevalence_full.jpg
                shoen_1: output/inc_no_adj_schoenfeld_res.csv
                shoen_2: output/inc_min_adj_schoenfeld_res.csv
                shoen_3: output/inc_full_adj_schoenfeld_res.csv
                shoen_4: output/prev_no_adj_schoenfeld_res.csv
                shoen_5: output/prev_min_adj_schoenfeld_res.csv
                shoen_6: output/prev_full_adj_schoenfeld_res.csv
                shoen_jp1: output/inc_no_adj_schoenfeld_res.jpg
                shoen_jp2: output/inc_min_adj_schoenfeld_res.jpg
                shoen_jp3: output/inc_full_adj_schoenfeld_res.jpg
                shoen_jp4: output/prev_no_adj_schoenfeld_res.jpg
                shoen_jp5: output/prev_min_adj_schoenfeld_res.jpg
                shoen_jp6: output/prev_full_adj_schoenfeld_res.jpg

    distribution_of_follow_up_time:
        run: r:latest analysis/11_distribution_of_follow_up_time.R
        needs: [cumulative_incidence]
        outputs:
            moderately_sensitive:
                distribution_inc: output/distribution_of_follow_up_time_incidence.jpg
                distribution_prev: output/distribution_of_follow_up_time_prevalence.jpg
                density1: output/distribution_of_follow_up_time_incidence_density.jpg
                density2: output/distribution_of_follow_up_time_prevalence_density.jpg
  
    event_rates_incidence:
        run: r:latest analysis/12_event_rates_incidence.R
        needs: [cumulative_incidence]
        outputs:
            moderately_sensitive:
                incidence_event_rates: output/event_counts_and_rates_incidence.csv

    event_rates_prevalence:
        run: r:latest analysis/13_event_rates_prevalence.R
        needs: [cumulative_incidence]
        outputs:
            moderately_sensitive:
                incidence_event_rates: output/event_counts_and_rates_prevalence.csv

    testing_interactions_and_anova:
        run: r:latest analysis/14_testing_interactions_and_anova.R
        needs: [cumulative_incidence]
        outputs:
            moderately_sensitive:
                d1: output/99_SCH_RESIDUALS_indextime_spline_interaction_INCIDENCE.jpg
                d2: output/99_COEFF_indextime_spline_interaction_INCIDENCE_full.csv
                d3: output/99_ANOVA_indextime_spline_interaction_INCIDENCE.csv
                d4: output/99_SCH_RESIDUALS_indextime_spline_interaction_INCIDENCE.csv
                d5: output/99_SCH_RESIDUALS_indextime_spline_interaction_PREVALENCE.jpg
                d6: output/99_SCH_RESIDUALS_indextime_spline_interaction_PREVALENCE.csv
                sc1: output/99_COEFF_indextime_spline_interaction_PREVALENCE.csv
                sc2: output/99_ANOVA_indextime_spline_interaction_PREVALENCE.csv
                sc3: output/99_SCH_RESIDUALS_waves_interaction_INCIDENCE.jpg
                sc4: output/99_ANOVA_waves_interaction_INCIDENCE.csv
                sc5: output/99_COEFF_waves_interaction_INCIDENCE.csv
                sc6: output/99_SCH_RESIDUALS_waves_interaction_INCIDENCE.csv

    #emmeans:
    #    run: r:latest analysis/15_emmeans.R
    #    needs: [cumulative_incidence]
    #    outputs:
    #        moderately_sensitive:
    #            d1: output/99_emmeans_incidence.csv
    #            d2: output/99_emmeans_incidence.jpg
    #            d3: output/99_emmeans_3df_incidence.csv
    #            d4: output/99_emmeans_3df_incidence.jpg
    #            d5: output/99_emmeans_4df_incidence.csv
    #            d6: output/99_emmeans_4df_incidence.jpg
    #            d7: output/BIC_all_3models.cvs
    #            d8: output/different_degrees_of_freedom_avova_all_adjustments.cvs

    #hr_for_interaction_with_spline:
    #    run: r:latest analysis/16_hr_for_interaction_with_spline.R
    #    needs: [cumulative_incidence]
    #    outputs:
    #        moderately_sensitive:
    #            d1: output/100_hazard_ratios_by_modifier_incidence.csv
    #            d2: output/100_hazard_ratios_by_modifier_variable.jpg

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:15:16

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
Klaudia Rzepnicka
Branch
main
Force run dependencies
No
Git commit hash
11d4565
Requested actions
  • descriptive_stats
  • cumulative_incidence
  • hazard_ratios
  • distribution_of_follow_up_time
  • event_rates_incidence
  • event_rates_prevalence
  • testing_interactions_and_anova

Code comparison

Compare the code used in this Job Request