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project.yaml
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project.yaml
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version: '3.0'
expectations:
population_size: 1000
actions:
# study cohort
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
process_1:
run: r:latest analysis/process_1.R
needs: [generate_study_population_covid_primarycare, generate_study_population_covid_SGSS,generate_study_population_covid_admission]
outputs:
highly_sensitive:
case: output/case_covid_hosp.csv
control: output/control_covid_infection.csv
# matching
matching: #R MatchIt matching with replacement
run: r:latest -e 'rmarkdown::render("analysis/matching.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
needs: [process_1]
outputs:
moderately_sensitive:
html: output/matching.html
highly_sensitive:
rds1: output/matched_patients.rds
rds2: output/unmatched_cases.rds
csv: output/matched_patients_id.csv # unique patient ID
check_unmatched:
run: r:latest -e 'rmarkdown::render("analysis/check_unmatched.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
needs: [matching]
outputs:
moderately_sensitive:
html: output/check_unmatched.html
extract_variables: # confounders
run: cohortextractor:latest generate_cohort --study-definition study_definition_outcome --with-end-date-fix
needs: [matching]
outputs:
highly_sensitive:
cohort: output/input_outcome.csv
process_Rmatching: # confounders
run: r:latest analysis/process_Rmatching.R
needs: [extract_variables,matching]
outputs:
highly_sensitive:
cohort1: output/matched_outcome.rds
cohort2: output/matched_outcome_check.rds # filter died & de-regist again
rds1: output/abtype79.rds
rds2: output/comor17.rds
# extract ab for RF
extract_variables_ab_time: # exposure variables
run: cohortextractor:latest generate_cohort --study-definition study_definition_ab_time --with-end-date-fix # unique matched patient ID
needs: [matching]
outputs:
highly_sensitive:
cohort: output/input_ab_time.csv
process_ab_time: # exposures #merge ab time with mathced patients
run: r:latest -e 'rmarkdown::render("analysis/process_ab_time.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
needs: [extract_variables_ab_time,process_Rmatching]
outputs:
moderately_sensitive:
html: output/process_ab_time.html
highly_sensitive:
rds: output/matched_ab.rds
model_RF_process: # merge 79 types of ab, split train and valid set
run: r:latest -e 'rmarkdown::render("analysis/model_RF_process.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [process_ab_time,process_Rmatching]
outputs:
moderately_sensitive:
html: output/model_RF_process.html
highly_sensitive:
rds1: output/train_X.rds
rds2: output/train_Y.rds
rds3: output/valid_X.rds
rds4: output/valid_Y.rds
rds5: output/abtype.rds
model_clogit: # coditional logistic regression for expo variables # create category variable
run: r:latest -e 'rmarkdown::render("analysis/model_clogit.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile,model_RF_process]
outputs:
moderately_sensitive:
html: output/model_clogit.html
rds1: output/train_cat.rds
rds2: output/valid_cat.rds
# classification_tree: #decision tree check # category
# run: r:latest -e 'rmarkdown::render("analysis/classification_tree.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_clogit]
# outputs:
# moderately_sensitive:
# html: output/classification_tree.html
classification_tree_ind: #decision tree check # category #uni+multi predictor #1:6 vs 1:1
run: r:latest -e 'rmarkdown::render("analysis/classification_tree_ind.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/classification_tree_ind.html
classification_tree_combined:
run: r:latest -e 'rmarkdown::render("analysis/classification_tree_combined.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/classification_tree_combined.html
# classification_tree_all: #decision tree check # category #all predictor
# run: r:latest -e 'rmarkdown::render("analysis/classification_tree_all.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_clogit]
# outputs:
# moderately_sensitive:
# html: output/classification_tree_all.html
# classification_tree_ind_rpart: #decision tree check # category #per predictor
# run: r:latest -e 'rmarkdown::render("analysis/classification_tree_ind_rpart.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_clogit]
# outputs:
# moderately_sensitive:
# html: output/classification_tree_ind_rpart.html
# classification_tree_contd: #decision tree check # contd
# run: r:latest -e 'rmarkdown::render("analysis/classification_tree_contd.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/classification_tree_contd.html
# model_tuneRF: #mtry,
# run: r:latest -e 'rmarkdown::render("analysis/model_tuneRF.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/model_tuneRF.html
# model_RF_training: #
# run: r:latest -e 'rmarkdown::render("analysis/model_RF_training.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/model_RF_training.html
model_RandomForest: # pick variables for model training # contd
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/model_RandomForest.html
# csv1: output/var_tree.csv
rds: output/model_RandomForest.rds
model_RandomForest_cat: # pick variables for model training # category #1:1 vs 1:6
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_cat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/model_RandomForest_cat.html
highly_sensitive:
rds: output/model_RandomForest_cat.rds
# train: output/train_6_cat.rds
# valid: output/valid_6_cat.rds
model_RandomForest_tune: # check prob
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_tune.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/model_RandomForest_tune.html
model_RF_weighted: # pick variables for model training # category
run: r:latest -e 'rmarkdown::render("analysis/model_RF_weighted.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/model_RF_weighted.html
highly_sensitive:
rds: output/model_RF_weighted.rds
model_RandomForest_check_cat: # check performance
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_check_cat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_cat]
outputs:
moderately_sensitive:
html: output/model_RandomForest_check_cat.html
model_RandomForest_cat_ind: # pick variables for model training # category #6:6 # individual variables
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_cat_ind.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit]
outputs:
moderately_sensitive:
html: output/model_RandomForest_cat_ind.html
model_RandomForest_decile_cat: # create decile groups for probabilities # get counfounders #6:6
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_decile_cat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_clogit,model_RandomForest_cat,model_RF_weighted]
outputs:
moderately_sensitive:
html: output/model_RandomForest_decile_cat.html
rds1: output/development_cat.rds
rds2: output/validation_cat.rds
model_cat: # coditional logistic regression for decile groups
run: r:latest -e 'rmarkdown::render("analysis/model_cat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile_cat]
outputs:
moderately_sensitive:
html: output/model_cat.html
RF_descriptive_stat_cat:
run: r:latest -e 'rmarkdown::render("analysis/RF_descriptive_stat_cat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile_cat]
outputs:
moderately_sensitive:
html: output/RF_descriptive_stat_cat.html
# model_RF_clust: # use proximity
# run: r:latest -e 'rmarkdown::render("analysis/model_RF_clust.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/model_RF_clust.html
# # csv1: output/var_tree.csv
# # rds: output/model_RandomForest.rds
model_RandomForest_check: # check performance
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_check.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,model_RandomForest]
outputs:
moderately_sensitive:
html: output/model_RandomForest_check.html
model_RandomForest_tree: # check tree
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_tree.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,model_RandomForest]
outputs:
moderately_sensitive:
html: output/model_RandomForest_tree.html
model_RandomForest_decile: # create decile groups for probabilities # get counfounders
run: r:latest -e 'rmarkdown::render("analysis/model_RandomForest_decile.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,model_RandomForest,process_ab_time,process_Rmatching]
outputs:
moderately_sensitive:
html: output/model_RandomForest_decile.html
rds1: output/development.rds
rds2: output/validation.rds
RF_descriptive_stat:
run: r:latest -e 'rmarkdown::render("analysis/RF_descriptive_stat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile]
outputs:
moderately_sensitive:
html: output/RF_descriptive_stat.html
model: # coditional logistic regression for decile groups
run: r:latest -e 'rmarkdown::render("analysis/model.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile]
outputs:
moderately_sensitive:
html: output/model.html
model_clogit_adjusted: # coditional logistic regression for expo variables
run: r:latest -e 'rmarkdown::render("analysis/model_clogit_adjusted.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile,model_RF_process]
outputs:
moderately_sensitive:
html: output/model_clogit_adjusted.html
model_logistic: # logistic regression for expo variables
run: r:latest -e 'rmarkdown::render("analysis/model_logistic.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RandomForest_decile,model_RF_process]
outputs:
moderately_sensitive:
html: output/model_logistic.html
## updated method
RF_model: # pick variables for model training #distinct # ab users # merge
run: r:latest -e 'rmarkdown::render("analysis/RF_model.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/RF_model.html
rds1: output/RF_model.rds
rds2: output/RF_model_decile.rds
RF_model_develop: # pick variables for model training #distinct # ab users # development
run: r:latest -e 'rmarkdown::render("analysis/RF_model_develop.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,RF_model]
outputs:
moderately_sensitive:
html: output/RF_model_develop.html
rds1: output/RF_model_develop.rds
rds2: output/RF_model_decile_develop.rds
RF_model_valid: # pick variables for model training #distinct # ab users # validation
run: r:latest -e 'rmarkdown::render("analysis/RF_model_valid.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,RF_model_develop]
outputs:
moderately_sensitive:
html: output/RF_model_valid.html
rds1: output/RF_model_decile_valid.rds
RF_classification_check:
run: r:latest -e 'rmarkdown::render("analysis/RF_classification_check.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,RF_model_develop,RF_model_valid]
outputs:
moderately_sensitive:
html: output/RF_classification_check.html
descriptive_stat:
run: r:latest -e 'rmarkdown::render("analysis/descriptive_stat.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,RF_model_develop,RF_model_valid]
outputs:
moderately_sensitive:
html: output/descriptive_stat.html
# # main analysis
table1_round:
run: r:latest analysis/table1.R
needs: [process_1,process_Rmatching]
outputs:
moderately_sensitive:
csv1: output/table1_unmatched.csv
csv2: output/table1_matched.csv
csv3: output/table1_random.csv
table2_round:
run: r:latest analysis/table2.R
needs: [process_Rmatching]
outputs:
moderately_sensitive:
csv1: output/table2_matched.csv
csv3: output/table2_random.csv
table3_round: # baseline table of exposure variables/ training &validation
run: r:latest analysis/table3.R
needs: [model_RF_process]
outputs:
moderately_sensitive:
csv1: output/table3_train.csv
csv2: output/table3_valid.csv
csv3: output/table3_all.csv
# variables check
check_variables: # check input
run: r:latest -e 'rmarkdown::render("analysis/check_variables.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/check_variables.html
###### random 1 control #####
classification_check: # RF # total_ab #1000trees used to compared with 6controls
run: r:latest -e 'rmarkdown::render("analysis/classification_check.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check.html
rds1: output/train_1control.rds
rds2: output/valid_1control.rds
classification_check_1_control: # RF # all # 1 control
run: r:latest -e 'rmarkdown::render("analysis/classification_check_1_control.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,classification_check]
outputs:
moderately_sensitive:
html: output/classification_check_1_control.html
classification_check_6_control: # RF # total_ab #1:6
run: r:latest -e 'rmarkdown::render("analysis/classification_check_6_control.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check_6_control.html
classification_check_logi: #logistic #6 controls
run: r:latest -e 'rmarkdown::render("analysis/classification_check_logi.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check_logi.html
classification_check_logi_1_control: #logistic # single control # decile
run: r:latest -e 'rmarkdown::render("analysis/classification_check_logi_1_control.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check_logi_1_control.html
#decile check
classification_check_logi_1_control_decile: #logistic # single control # total ab decile
run: r:latest -e 'rmarkdown::render("analysis/classification_check_logi_1_control_decile.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check_logi_1_control_decile.html
classification_check_1_control_decile: # RF # all # 1 control # total ab decile
run: r:latest -e 'rmarkdown::render("analysis/classification_check_1_control_decile.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,classification_check]
outputs:
moderately_sensitive:
html: output/classification_check_1_control_decile.html
# remove outlier
classification_check_1_control_0.9: # RF # all # 1 control # remove90th outlier
run: r:latest -e 'rmarkdown::render("analysis/classification_check_1_control_0.9.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,classification_check]
outputs:
moderately_sensitive:
html: output/classification_check_1_control_0.9.html
classification_check_logi_1_control_0.9: #logistic # single control remove90th outlier
run: r:latest -e 'rmarkdown::render("analysis/classification_check_logi_1_control_0.9.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/classification_check_logi_1_control_0.9.html
# classification_check_logi_1_decile: #logistic # single control # decile group
# run: r:latest -e 'rmarkdown::render("analysis/classification_check_logi_1_control_decile.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/classification_check_logi_1_control_decile.html
# distinct
model_RF_distinct: # pick variables for model training # distinct patients
run: r:latest -e 'rmarkdown::render("analysis/model_RF_distinct.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/model_RF_distinct.html
rds: output/model_RF_distinct.rds
model_RF_distinct_check:
run: r:latest -e 'rmarkdown::render("analysis/model_RF_distinct_check.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,model_RF_distinct]
outputs:
moderately_sensitive:
html: output/model_RF_distinct_check.html
# random 1 control
model_RF_random_1_control: # random pick one control in subclass
run: r:latest -e 'rmarkdown::render("analysis/model_RF_random_1_control.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process]
outputs:
moderately_sensitive:
html: output/model_RF_random_1_control.html
rds: output/model_RF_random_1_control.rds
model_RF_random_1_control_check:
run: r:latest -e 'rmarkdown::render("analysis/model_RF_random_1_control_check.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
needs: [model_RF_process,model_RF_random_1_control]
outputs:
moderately_sensitive:
html: output/model_RF_random_1_control_check.html
# #######
# model_tuneRF: #
# run: r:latest -e 'rmarkdown::render("analysis/model_tuneRF.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [model_RF_process]
# outputs:
# moderately_sensitive:
# html: output/model_tuneRF.html
# check_ab_time:
# run: r:latest -e 'rmarkdown::render("analysis/check_ab_time.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [process_ab_time]
# outputs:
# moderately_sensitive:
# html: output/check_ab_time.html
# # highly_sensitive:
# # rds: output/matched_patients_monthly_ab.rds
# check_RF_grid:
# run: r:latest -e 'rmarkdown::render("analysis/check_RF_grid.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [process_ab_time]
# outputs:
# moderately_sensitive:
# html: output/check_RF_grid.html
# check_RF:
# run: r:latest -e 'rmarkdown::render("analysis/check_RF.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [process_ab_time]
# outputs:
# moderately_sensitive:
# html: output/check_RF.html
# model_RF:
# run: r:latest -e 'rmarkdown::render("analysis/model_RF.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [process_ab_time]
# outputs:
# moderately_sensitive:
# html: output/model_RF.html
# model_RF_process_subclass: # random sampling by subclass
# run: r:latest -e 'rmarkdown::render("analysis/model_RF_process_subclass.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [process_ab_time]
# outputs:
# moderately_sensitive:
# html: output/model_RF_process_subclass.html
# model_RF_process_check_sample: # check sample method
# run: r:latest -e 'rmarkdown::render("analysis/model_RF_process_check_sample.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [process_ab_time, process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/model_RF_process_check_sample.html
# # check
# process_filter_ab: # filter ab users
# run: r:latest -e 'rmarkdown::render("analysis/process_filter_ab.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/process_filter_ab.html
# highly_sensitive:
# csv: output/matched_patients_id_ab.csv
# extract_variables_ab_yr1:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_ab_yr1 --with-end-date-fix
# needs: [process_filter_ab]
# outputs:
# highly_sensitive:
# cohort: output/input_ab_yr1.csv
# extract_variables_ab_yr2:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_ab_yr2 --with-end-date-fix
# needs: [process_filter_ab]
# outputs:
# highly_sensitive:
# cohort: output/input_ab_yr2.csv
# extract_variables_ab_yr3:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_ab_yr3 --with-end-date-fix
# needs: [process_filter_ab]
# outputs:
# highly_sensitive:
# cohort: output/input_ab_yr3.csv
# extract_variables_ab_yr3_15d:
# run: cohortextractor:latest generate_cohort --study-definition study_definition_ab_yr3_15d --with-end-date-fix
# needs: [process_filter_ab]
# outputs:
# highly_sensitive:
# cohort: output/input_ab_yr3_15d.csv
# process_merge_ab: # merge 1-2-3 year ab
# run: r:latest -e 'rmarkdown::render("analysis/process_merge_ab.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [process_Rmatching,extract_variables_ab_yr3_15d, extract_variables_ab_yr3,extract_variables_ab_yr2,extract_variables_ab_yr1]
# outputs:
# moderately_sensitive:
# html: output/process_merge_ab.html
# highly_sensitive:
# rds: output/matched_patients_monthly_ab.rds
# check_ab_yr1:
# run: r:latest -e 'rmarkdown::render("analysis/check_ab_yr1.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [extract_variables_ab_yr1,matching,process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/check_ab_yr1.html
# check_ab_yr3:
# run: r:latest -e 'rmarkdown::render("analysis/check_ab_yr3.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/check_ab_yr3.html
# check_abtype:
# run: r:latest -e 'rmarkdown::render("analysis/check_abtype.Rmd", knit_root_dir = "/workspace", output_dir="/workspace/output")'
# needs: [process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/check_abtype.html
# check_process_1:
# run: r:latest -e 'rmarkdown::render("analysis/check_process_1.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [generate_study_population_covid_primarycare,generate_study_population_covid_SGSS,generate_study_population_covid_admission]
# outputs:
# moderately_sensitive:
# html: output/check_process_1.html
# # check_RF:
# # run: r:latest -e 'rmarkdown::render("analysis/check_RF.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# # needs: [process_Rmatching]
# # outputs:
# # moderately_sensitive:
# # html: output/check_RF.html
# # check_RF_grid:
# # run: r:latest -e 'rmarkdown::render("analysis/check_RF_grid.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# # needs: [process_Rmatching]
# # outputs:
# # moderately_sensitive:
# # html: output/check_RF_grid.html
# check_RF_yr1:
# run: r:latest -e 'rmarkdown::render("analysis/check_RF_yr1.Rmd", knit_root_dir = "/workspace", output_dir = "output")'
# needs: [extract_variables_ab_yr1,matching,process_Rmatching]
# outputs:
# moderately_sensitive:
# html: output/check_RF_yr1.html