Job request: 6358
- Organisation:
- QMUL
- Workspace:
- bmi-and-metabolic-markers
- ID:
- hazn2zy77czfstxr
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
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various outputs were written to. Researchers can never directly
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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
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can be requested for release to the public, via a controlled
output review service.
Jobs
-
- Job identifier:
-
5kkpfvuvbjuzstlh
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 50000
actions:
### 1. Extract the cohort
## 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"" --output-format feather
generate_study_population_1:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2015-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2015-03-01.feather
generate_study_population_2:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2016-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2016-03-01.feather
generate_study_population_3:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2017-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2017-03-01.feather
generate_study_population_4:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2018-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2018-03-01.feather
generate_study_population_5:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2019-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2019-03-01.feather
generate_study_population_6:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2020-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2020-03-01.feather
generate_study_population_7:
run: cohortextractor:latest generate_cohort --study-definition study_definition_all --output-dir=output/data --index-date-range "2021-03-01" --output-format feather
outputs:
highly_sensitive:
cohort: output/data/input_all_2021-03-01.feather
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.feather
join_ethnicity:
run: python:latest python analysis/join_ethnicity.py --output-dir=output/data --output-format feather
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*.feather
### Develop yearly BMI data sets to de-duplicate data and calculate median BMI each year. Feather format to reduce data quantity.
generate_BMI_2015_data:
run: r:latest analysis/BMI_2015.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2015.feather
cohort2: output/data/BMI_complete_long_2015.feather
generate_BMI_2016_data:
run: r:latest analysis/BMI_2016.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2016.feather
cohort2: output/data/BMI_complete_long_2016.feather
generate_BMI_2017_data:
run: r:latest analysis/BMI_2017.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2017.feather
cohort2: output/data/BMI_complete_long_2017.feather
generate_BMI_2019_data:
run: r:latest analysis/BMI_2019.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2019.feather
cohort2: output/data/BMI_complete_long_2019.feather
generate_BMI_2021_data:
run: r:latest analysis/BMI_2021.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2021.feather
cohort2: output/data/BMI_complete_long_2021.feather
generate_BMI_2018_data:
run: r:latest analysis/BMI_2018.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2018.feather
cohort2: output/data/BMI_complete_long_2018.feather
generate_BMI_2020_data:
run: r:latest analysis/BMI_2020.R --output-dir=output/data --output-format feather
needs: [join_ethnicity]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median_2020.feather
cohort2: output/data/BMI_complete_long_2020.feather
# Append yearly data sets to produce a complete data set for analysis of change in trends
generate_complete_median_BMI_data:
run: r:latest analysis/BMI_median_combine_datasets.R --output-dir=output/data --output-format feather
needs: [generate_BMI_2015_data, generate_BMI_2016_data, generate_BMI_2017_data, generate_BMI_2018_data, generate_BMI_2019_data, generate_BMI_2020_data, generate_BMI_2021_data ]
outputs:
highly_sensitive:
cohort1: output/data/BMI_complete_median.feather
#############################################################################################
### >> CREATE DATA SET WITH BMI AND WHOLE POPULATION DATA TO ASSESS ODDS OF HAVING BMI TEST
##############################################################################################
generate_whole_pop_2019:
run: r:latest analysis/create_BMI_all_2019.R --output-dir=output/data --output-format feather
needs: [join_ethnicity, generate_BMI_2019_data]
outputs:
highly_sensitive:
cohort1: output/data/BMI_all_2019.feather
generate_whole_pop_2020:
run: r:latest analysis/create_BMI_all_2020.R --output-dir=output/data --output-format feather
needs: [join_ethnicity, generate_BMI_2020_data, generate_complete_median_BMI_data]
outputs:
highly_sensitive:
cohort1: output/data/BMI_all_2020.feather
generate_whole_pop_2021:
run: r:latest analysis/create_BMI_all_2021.R --output-dir=output/data --output-format feather
needs: [join_ethnicity, generate_BMI_2021_data, generate_complete_median_BMI_data]
outputs:
highly_sensitive:
cohort1: output/data/BMI_all_2021.feather
##################################################################
### >> HAD_BMI ANALYSIS
######################################################################
# who had_bmi measured: univariate and multivariate analysis and tables
generate_had_bmi_proportion_2019:
run: r:latest analysis/had_bmi_proportions_2019.R --output-dir=output/data
needs: [generate_whole_pop_2019]
outputs:
moderately_sensitive:
table1: output/data/proportion_had_bmi_2019.csv
generate_had_bmi_proportion_2020:
run: r:latest analysis/had_bmi_proportions_2020.R --output-dir=output/data
needs: [generate_whole_pop_2020]
outputs:
moderately_sensitive:
table1: output/data/proportion_had_bmi_2020.csv
generate_had_bmi_proportion_2021:
run: r:latest analysis/had_bmi_proportions_2021.R --output-dir=output/data
needs: [generate_whole_pop_2021]
outputs:
moderately_sensitive:
table1: output/data/proportion_had_bmi_2021.csv
#########################################################
## PROPORTION OBESE ANALYSIS
generate_obese_proportion_2019:
run: r:latest analysis/obese_proportions_2019.R --output-dir=output/data
needs: [generate_whole_pop_2019]
outputs:
moderately_sensitive:
table1: output/data/proportion_obese_2019.csv
######################################################################################
# >> Median BMI Analysis
#######################################################################################
# generate summary stats of median BMI by exposures
generate_median_summary_stats:
run: r:latest analysis/BMI_median_summary_stats.R --output-dir=output/data
needs: [generate_complete_median_BMI_data]
outputs:
moderately_sensitive:
table1: output/data/median_bmi_summary_table_demographic.csv
table2: output/data/median_bmi_summary_table_covariates.csv
Timeline
-
Created:
-
Finished:
-
Runtime:
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
- 73485be
- Requested actions
-
-
generate_obese_proportion_2019
-
Code comparison
Compare the code used in this Job Request