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Job request: 5889

Organisation:
QMUL
Workspace:
bmi-and-metabolic-markers
ID:
45cjlh63dgrpojdd
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Miriam Samuel 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:



  ## use the Measure function to allow data for different time periods to be extracted in the same study population:  --index-date-range ""yyyy-mm-dd""   
  generate_study_population_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2015-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2015-03-01.csv  

  generate_study_population_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2016-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2016-03-01.csv  

  generate_study_population_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2017-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2017-03-01.csv  
        
  generate_study_population_4:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2018-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2018-03-01.csv  
        
        
  generate_study_population_5:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2019-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2019-03-01.csv        
        
  generate_study_population_6:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2020-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2020-03-01.csv  
   
  generate_study_population_7:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2021-03-01"
    outputs:
      highly_sensitive:
        cohort: output/data/input_all_2021-03-01.csv  
 
 

  generate_study_population_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output/data #--output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/data/input_ethnicity.csv
        
      
        
        
        
  join_ethnicity:
    run: python:latest python analysis/join_ethnicity.py --output-dir=output/data
    needs: [generate_study_population_1, generate_study_population_2, generate_study_population_3, generate_study_population_4, generate_study_population_5, generate_study_population_6, generate_study_population_7, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/data/input*.csv


  generate_BMI_complete_categories:
    run: r:latest analysis/BMI.R --output-dir=output/data
    needs: [join_ethnicity]
    outputs:
      highly_sensitive:
        cohort1: output/data/BMI_complete_categories.csv
        cohort2: output/data/BMI_complete_long.csv
        
  BMI_recorded_analysis:
    run: r:latest analysis/BMI_recorded_summary.R --output-dir=output/data
    needs: [generate_BMI_complete_categories]
    outputs:
      moderately_sensitive:
        table: output/data/BMI_recorded_summary_covariates.csv
             
  
  had_bmi_regression:    
    run: r:latest analysis/had_bmi_regression.R --output-dir=output/data
    needs: [generate_BMI_complete_categories]
    outputs:
      moderately_sensitive:
        table1: output/data/regression_had_bmi_2020.csv
        table2: output/data/regression_had_bmi_2021.csv
        table3: output/data/multivariate_regression_had_bmi_2020.csv
        table4: output/data/multivariate_regression_had_bmi_2021.csv

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 03:51:18

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

Job information

Status
Failed
Backend
TPP
Workspace
bmi-and-metabolic-markers
Requested by
Miriam Samuel
Branch
main
Force run dependencies
No
Git commit hash
9df6c98
Requested actions
  • generate_BMI_complete_categories

Code comparison

Compare the code used in this Job Request