R/hello.R

In ohdsi-studies/OT2DSI: Observational Study of Type 2 Diabetes and its Complications: A Chronological Overview Using the OHDSI Network

# Some useful keyboard shortcuts for package authoring:
#
#   Install Package:           'Ctrl + Shift + B'
#   Check Package:             'Ctrl + Shift + E'
#   Test Package:              'Ctrl + Shift + T'

execute <- function(connection,
                    cdmDatabaseSchema,
                    targetDatabaseSchema,
                    cohortTable,
                    oracleTempSchema,
                    outputFolder,
                    createCohorts,
                    generatePathways,
                    plotResults,
                    getCharacterization,
                    getIncidenceRates){


  ### Create output directory
  folder <- "output"
  dir.create(folder, showWarnings = FALSE)
  output_folder <- paste0(folder,"/",outputFolder)
  dir.create(output_folder, showWarnings = FALSE)


  ### createCohorts
  if(createCohorts){

    .createCohorts(connection,
                   cdmDatabaseSchema,
                   vocabularyDatabaseSchema = cdmDatabaseSchema,
                   cohortDatabaseSchema = targetDatabaseSchema,
                   cohortTable = cohortTable,
                   oracleTempSchema = oracleTempSchema,
                   output_folder)
  }


  ### Read pathway JSON
  pathwayDef <- jsonlite::read_json(system.file("settings", "pathwaySpecification.json", package = "OT2DSI"))

  ### Read names of cohort to create
  pathwaysCohorts <- read.csv(system.file("settings", "CohortsToCreate.csv", package = "OT2DSI"))

  event_cohort_id_index_map <- pathwaysCohorts %>%
    filter(cohortType == 1) %>%
    rename(cohort_definition_id = cohortId) %>%
    mutate(cohort_index = row_number() - 1) %>%
    mutate(atlasName = stringr::str_replace(atlasName,'OT2DSI_','')) %>%
    select(cohort_definition_id, cohort_index, atlasName) %>%
    as.data.frame()

  event_cohort_id_index_map <- event_cohort_id_index_map %>% mutate(powered_index = 2^cohort_index)

  write.csv(event_cohort_id_index_map, file.path("inst/settings", "cohort_id_index_map.csv"), row.names = F)

  ### Create target cohort data frame
  target_cohorts <- pathwaysCohorts %>%
    filter(cohortType == 0) %>%
    select(cohortId, atlasName) %>%
    rename(cohort_definition_id = cohortId, name = atlasName)


  ### generatePathways
  if(generatePathways){

          .generatePathways(connection,
                            cdmDatabaseSchema = cdmDatabaseSchema,
                            targetDatabaseSchema = targetDatabaseSchema,
                            cohortTable = cohortTable,
                            event_cohort_id_index_map,
                            target_cohorts,
                            pathwayDef,
                            oracleTempSchema,
                            output_folder = output_folder)
  }


  ### plotResults
  if(plotResults){

              .plotResults(connection,
                            cdmDatabaseSchema,
                            vocabularyDatabaseSchema = cdmDatabaseSchema,
                            cohortDatabaseSchema = targetDatabaseSchema,
                            cohortTable = cohortTable,
                            oracleTempSchema,
                            output_folder = output_folder)
  }


  ### getCharacterization
  if (getCharacterization) {

      .getCohortCharacteristics (connectionDetails = connectionDetails,
                                 connection = connection,
                                 cdmDatabaseSchema,
                                 oracleTempSchema ,
                                 cohortDatabaseSchema = cdmDatabaseSchema,
                                 cohortTable = cohortTable,
                                 cohortId = 1,
                                 minCellCount = pathwayDef$minCellCount,
                                 output_folder = output_folder)
  }


  ### getIncidenceRates
  if (getIncidenceRates) {

      .getIncidenceRates (connectionDetails = connectionDetails,
                          connection = connection,
                          targetDatabaseSchema,
                          cdmDatabaseSchema,
                          oracleTempSchema,
                          cohortTable = cohortTable,
                          output_folder = output_folder)
  }

  ### Zip output folder
  .zip_folder(output_folder ,paste0("output_",outputFolder,".zip"))

  DatabaseConnector::disconnect(connection)
}

#
#
#

.extract_bitSum <- function(x) {

  series <- c(2^(0:20))

  remainder = x
  combination = c()

  while(remainder != 0){

    component = match(TRUE, series > remainder) - 1

    remainder = remainder - series[component]

    combination[length(combination)+1] <- component - 1

  }

  return(combination)

}