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Job request: 8048

Organisation:
Bennett Institute
Workspace:
bmi-short-data-report
ID:
vnojx63yywyd2uv4
View repo View project.yaml

This page shows the technical details of what happened when the authorised researcher Robin Park requested one or more actions to be run against real patient data within a secure environment.

By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.

The output security levels are:

  • highly_sensitive
    • Researchers can never directly view these outputs
    • Researchers can only request code is run against them
  • moderately_sensitive
    • Can be viewed by an approved researcher by logging into a highly secure environment
    • These are the only outputs that can be requested for public release via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 1000

actions:

  generate_event_counts:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_eventcounts --output-dir=output/data --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/data/input_eventcounts.feather

  generate_study_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --output-dir=output/data --output-format feather
    outputs:
      highly_sensitive:
        cohort: output/data/input.feather

  preprocess_inputs:
    run: python:latest python analysis/preprocess_inputs.py --output-format feather
    needs: [generate_study_population]
    outputs:
      highly_sensitive:
        cohort_with_duration: output/data/input_processed.feather

  execute_validation_analyses:
    run: python:latest python analysis/validation_script.py
    needs: [preprocess_inputs]
    outputs:
      moderately_sensitive: 
        tables: output/phenotype_validation_bmi/tables/*.csv
        figures: output/phenotype_validation_bmi/figures/*.png
        
  generate_report_bmi:
    run: python:latest jupyter nbconvert /workspace/notebooks/report_bmi.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [execute_validation_analyses]
    outputs:
      moderately_sensitive:
        notebook: output/report_bmi.html
        
  execute_validation_analyses_height:
    run: python:latest python analysis/validation_script_height.py
    needs: [preprocess_inputs]
    outputs:
      moderately_sensitive: 
        tables: output/phenotype_validation_height/tables/*.csv
        figures: output/phenotype_validation_height/figures/*.png
        
  generate_report_height:
    run: python:latest jupyter nbconvert /workspace/notebooks/report_height.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [execute_validation_analyses_height]
    outputs:
      moderately_sensitive:
        notebook: output/report_height.html
        
  execute_validation_analyses_weight:
    run: python:latest python analysis/validation_script_weight.py
    needs: [preprocess_inputs]
    outputs:
      moderately_sensitive: 
        tables: output/phenotype_validation_weight/tables/*.csv
        figures: output/phenotype_validation_weight/figures/*.png
        
  generate_report_weight:
    run: python:latest jupyter nbconvert /workspace/notebooks/report_weight.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [execute_validation_analyses_weight]
    outputs:
      moderately_sensitive:
        notebook: output/report_weight.html
        
  generate_histograms:
    run: python:latest python analysis/validation_histograms.py
    needs: [preprocess_inputs]
    outputs:
      moderately_sensitive: 
        tables1: output/histograms/tables/hist*.csv
        tables2: output/histograms/tables/ct*.csv
        figures1: output/histograms/figures/hist*.png
        figures2: output/histograms/figures/cdf*.png
 
  execute_validation_recency:
    run: python:latest python analysis/validation_recency.py
    needs: [preprocess_inputs]
    outputs:
      moderately_sensitive: 
        tables: output/histograms/tables/*.csv
        figures: output/histograms/figures/*.png
  
  generate_report_eventcounts:
    run: python:latest jupyter nbconvert /workspace/notebooks/report_event_counts.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs: [generate_event_counts]
    outputs:
      moderately_sensitive:
        notebook: output/report_event_counts.html

  generate_dataset_report:
    run: >
      dataset-report:v0.0.9
        --input-files output/data/input.feather
        --output-dir output/data
    needs: [generate_study_population]
    outputs:
      moderately_sensitive:
        dataset_report: output/data/input.html

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:05:54

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

Job request

Status
Succeeded
Backend
TPP
Workspace
bmi-short-data-report
Requested by
Robin Park
Branch
main
Force run dependencies
No
Git commit hash
327f665
Requested actions
  • generate_dataset_report

Code comparison

Compare the code used in this job request