Job request: 5382
- Organisation:
- University of Manchester
- Workspace:
- brit_cc_v2
- ID:
- txwq7sgbnou4fiby
This page shows the technical details of what happened when the authorised researcher Ya-Ting Yang 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
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Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population:
run: cohortextractor:latest generate_cohort --study-definition study_definition_general_population
outputs:
highly_sensitive:
cohort: output/input_general_population.csv
generate_study_population_covid_primarycare:
run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_primarycare
outputs:
highly_sensitive:
cohort: output/input_covid_primarycare.csv
generate_study_population_covid_SGSS:
run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_SGSS
outputs:
highly_sensitive:
cohort: output/input_covid_SGSS.csv
generate_study_population_covid_admission:
run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_admission
outputs:
highly_sensitive:
cohort: output/input_covid_admission.csv
# generate_study_population_covid_icu:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_icu
# outputs:
# highly_sensitive:
# cohort: output/input_covid_icu.csv
generate_study_population_covid_death_ons:
run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_death_ons
outputs:
highly_sensitive:
cohort: output/input_covid_death_ons.csv
generate_study_population_covid_death_cpns:
run: cohortextractor:latest generate_cohort --study-definition study_definition_covid_death_cpns
outputs:
highly_sensitive:
cohort: output/input_covid_death_cpns.csv
process:
run: r:latest analysis/process.R
needs: [generate_study_population_covid_primarycare, generate_study_population_covid_SGSS,generate_study_population_covid_admission,generate_study_population_covid_death_ons,generate_study_population_covid_death_cpns]
outputs:
highly_sensitive:
cohort1.1: output/case_covid_infection.csv
cohort1.2: output/control_covid_infection.csv
#cohort1.3: output/case_covid_infection_*.csv # for monthly matching
cohort2: output/case_covid_admission.csv
cohort3: output/case_covid_icu_death.csv
matching_1:
run: python:latest python analysis/matching_outcome_1.py
needs: [generate_study_population, process]
outputs:
moderately_sensitive:
matching_report1: output/matching_report_general_population_infection.txt
highly_sensitive:
combined1: output/matched_combined_general_population_infection.csv
matching_2:
run: python:latest python analysis/matching_outcome_2.py
needs: [process]
outputs:
moderately_sensitive:
matching_report2: output/matching_report_infection_hosp.txt
highly_sensitive:
combined2: output/matched_combined_infection_hosp.csv
matching_3:
run: python:latest python analysis/matching_outcome_3.py
needs: [process]
outputs:
moderately_sensitive:
matching_report3: output/matching_report_hosp_icu_death.txt
highly_sensitive:
combined3: output/matched_combined_hosp_icu_death.csv
extract_variables_outcome_1:
run: cohortextractor:latest generate_cohort --study-definition study_definition_outcome_1
needs: [matching_1]
outputs:
highly_sensitive:
cohort: output/input_outcome_1.csv
extract_variables_outcome_2:
run: cohortextractor:latest generate_cohort --study-definition study_definition_outcome_2
needs: [matching_2]
outputs:
highly_sensitive:
cohort: output/input_outcome_2.csv
extract_variables_outcome_3:
run: cohortextractor:latest generate_cohort --study-definition study_definition_outcome_3
needs: [matching_3]
outputs:
highly_sensitive:
cohort: output/input_outcome_3.csv
# variables:
# run: r:latest analysis/variables.R
# needs: [matching_1,matching_2,matching_3,extract_variables_outcome_1,extract_variables_outcome_2,extract_variables_outcome_3]
# outputs:
# highly_sensitive:
# cohort1: output/matched_outcome1.csv
# cohort2: output/matched_outcome2.csv
# cohort3: output/matched_outcome3.csv
# # cohort1.3: output/case_covid_infection_*.csv # for monthly matching
# # cohort2: output/case_covid_admission.csv
# # cohort3: output/case_covid_icu_death.csv
# rmd_report:
# run: r:latest -e 'rmarkdown::render("analysis/matching_report.Rmd", knit_root_dir
# = "/workspace", output_dir = "/workspace/output/report", output_format = c("html_document") )'
# needs: [variables]
# outputs:
# moderately_sensitive:
# html: output/report/matching_report.html
# ## monthly matching datasets
# generate_study_population_month:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_general_population --index-date-range "2020-02-01 to 2021-12-01 by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
# outputs:
# highly_sensitive:
# cohort: output/measures/input_general_population_*.csv.gz
# exclusion:
# run: r:latest analysis/exclusion.R
# needs: [process, generate_study_population_month]
# outputs:
# highly_sensitive:
# cohort4: output/control_general_population_*.csv
Timeline
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Created:
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Started:
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Finished:
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Runtime: 177:47:01
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
- Backend
- TPP
- Workspace
- brit_cc_v2
- Requested by
- Ya-Ting Yang
- Branch
- CC_AB_covid_V2
- Force run dependencies
- No
- Git commit hash
- b4e6e65
- Requested actions
-
-
run_all
-
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