Job request: 6825
- Organisation:
- Bennett Institute
- Workspace:
- covid_mortality_over_time
- ID:
- 5fe6lwbfkcm2poq6
This page shows the technical details of what happened when the authorised researcher Linda Nab 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
-
- Job identifier:
-
qaz4smnsqeo7cmkr
-
- Job identifier:
-
5z7ytwio5bzk3o4b
-
- Job identifier:
-
hrjk5boifqmqkpvc
-
- Job identifier:
-
2zxgpsj7nedwnehh
-
- Job identifier:
-
5bhgrt5rf5w2u2ja
-
- Job identifier:
-
moktudlkkjqwqvih
-
- Job identifier:
-
eolhrb3sauaa4yh2
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000
actions:
# Extract data
# When argument --index-date-range is changed, change has to be made in ./analysis/config.json too
generate_study_population:
run: >
cohortextractor:latest generate_cohort
--study-definition study_definition
--skip-existing
--output-format=csv.gz
--index-date-range "2020-03-01 to 2022-02-01 by month"
outputs:
highly_sensitive:
cohort: output/input_*.csv.gz
# Extract ethnicity
generate_study_population_ethnicity:
run: >
cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/input_ethnicity.csv.gz
# Join data
join_cohorts:
run: >
cohort-joiner:v0.0.7
--lhs output/input_202*.csv.gz
--rhs output/input_ethnicity.csv.gz
--output-dir=output/joined
needs: [generate_study_population, generate_study_population_ethnicity]
outputs:
highly_sensitive:
cohort: output/joined/input_202*.csv.gz
# Calculate mortality rates (crude + subgroup specific)
calculate_measures:
run: >
cohortextractor:latest generate_measures
--study-definition study_definition
--skip-existing
--output-dir=output/joined
needs: [join_cohorts]
outputs:
moderately_sensitive:
measure: output/joined/measure_*_mortality_rate.csv
# Standardise crude mortality rate
standardise_crude_rates:
run: r:latest analysis/crude_rates_standardise.R
needs: [calculate_measures]
outputs:
moderately_sensitive:
csvs: output/rates/crude_*monthly_std.csv
# Standardise subgroup specific mortality rates
standardise_subgroup_rates:
run: r:latest analysis/subgroups_rates_standardise.R
needs: [calculate_measures]
outputs:
moderately_sensitive:
csvs: output/rates/*_monthly_std.csv
# Process subgroup specific mortality rates
process_subgroup_rates:
run: r:latest analysis/utils/process_rates.R
needs: [standardise_subgroup_rates, standardise_subgroup_rates]
outputs:
moderately_sensitive:
csvs: output/rates/processed/*_monthly_std.csv
# Calculate standardised rate ratios
calculate_rate_ratios:
run: r:latest analysis/subgroups_ratios.R
needs: [standardise_subgroup_rates, process_subgroup_rates]
outputs:
moderately_sensitive:
csvs: output/ratios/*.csv
# Plot and save graphs depicting the crude rates
visualise_crude_rates:
run: r:latest analysis/crude_rates_visualise.R
needs: [standardise_crude_rates]
outputs:
moderately_sensitive:
pngs: output/figures/rates_crude/*.png
# Plot and save graphs depicting the subgroup specific mortality rates
visualise_subgroup_rates:
run: r:latest analysis/subgroups_rates_visualise.R
needs: [standardise_subgroup_rates, process_subgroup_rates]
outputs:
moderately_sensitive:
pngs: output/figures/rates_subgroups/*.png
# Plot and save graphs depicting the subgroup specific mortality ratios
visualise_subgroup_ratios:
run: r:latest analysis/subgroups_ratios_visualise.R
needs: [calculate_rate_ratios]
outputs:
moderately_sensitive:
pngs: output/figures/ratios_subgroups/*.png
# SECOND PART OF STUDY
generate_study_population_wave1:
run: >
cohortextractor:latest generate_cohort
--study-definition study_definition_wave1
--skip-existing
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/input_wave1.csv.gz
generate_study_population_wave2:
run: >
cohortextractor:latest generate_cohort
--study-definition study_definition_wave2
--skip-existing
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/input_wave2.csv.gz
generate_study_population_wave3:
run: >
cohortextractor:latest generate_cohort
--study-definition study_definition_wave3
--skip-existing
--output-format=csv.gz
outputs:
highly_sensitive:
cohort: output/input_wave3.csv.gz
# Join data
join_cohorts_waves:
run: >
cohort-joiner:v0.0.7
--lhs output/input_wave*.csv.gz
--rhs output/input_ethnicity.csv.gz
--output-dir=output/joined
needs: [generate_study_population_wave1, generate_study_population_wave2, generate_study_population_wave3, generate_study_population_ethnicity]
outputs:
highly_sensitive:
cohort: output/joined/input_wave*.csv.gz
# Process data
process_data:
run: r:latest analysis/data_process.R
needs: [join_cohorts_waves]
outputs:
highly_sensitive:
rds: output/processed/input_wave*.rds
# Create table one
create_table_one:
run: r:latest analysis/table_one.R
needs: [process_data]
outputs:
moderately_sensitive:
html: output/tables/table1.html
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 22:11:15
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
- Backend
- TPP
- Workspace
- covid_mortality_over_time
- Requested by
- Linda Nab
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 430a8c3
- Requested actions
-
-
generate_study_population
-
generate_study_population_ethnicity
-
join_cohorts
-
generate_study_population_wave1
-
generate_study_population_wave2
-
generate_study_population_wave3
-
join_cohorts_waves
-
Code comparison
Compare the code used in this Job Request