diff --git a/DESCRIPTION b/DESCRIPTION index 0aec09b29..52d02780e 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -21,7 +21,7 @@ Description: CohortDiagnostics is an R utility package for the development and e definitions across one or more data sources, facilitating reproducible research. Depends: DatabaseConnector (>= 5.0.0), - FeatureExtraction (>= 3.4.0), + FeatureExtraction (>= 3.5.0), R (>= 4.1.0) Imports: Andromeda (>= 0.6.0), diff --git a/R/CohortCharacterizationDiagnostics.R b/R/CohortCharacterizationDiagnostics.R index 25cee0834..537e0d2c4 100644 --- a/R/CohortCharacterizationDiagnostics.R +++ b/R/CohortCharacterizationDiagnostics.R @@ -23,7 +23,8 @@ getCohortCharacteristics <- function(connectionDetails = NULL, cohortIds, cdmVersion = 5, covariateSettings, - exportFolder) { + exportFolder, + minCharacterizationMean = 0.001) { startTime <- Sys.time() if (is.null(connection)) { connection <- DatabaseConnector::connect(connectionDetails) @@ -46,7 +47,8 @@ getCohortCharacteristics <- function(connectionDetails = NULL, cohortTable = cohortTable, cohortIds = cohortIds, covariateSettings = covariateSettings, - aggregated = TRUE + aggregated = TRUE, + minCharacterizationMean = minCharacterizationMean ) } ) @@ -289,7 +291,8 @@ executeCohortCharacterization <- function(connection, cohortIds = subset[start:end, ]$cohortId, covariateSettings = covariateSettings, cdmVersion = cdmVersion, - exportFolder = exportFolder + exportFolder = exportFolder, + minCharacterizationMean = minCharacterizationMean ) on.exit(Andromeda::close(characteristics), add = TRUE) @@ -303,7 +306,6 @@ executeCohortCharacterization <- function(connection, analysisRefFileName = analysisRefFileName, timeRefFileName = timeRefFileName, counts = cohortCounts, - minCharacterizationMean = minCharacterizationMean, minCellCount = minCellCount ) diff --git a/R/ExportCharacterization.R b/R/ExportCharacterization.R index e5323a2ab..8dcd2eec4 100644 --- a/R/ExportCharacterization.R +++ b/R/ExportCharacterization.R @@ -24,14 +24,12 @@ exportCharacterization <- function(characteristics, analysisRefFileName, timeRefFileName = NULL, counts, - minCharacterizationMean = 0.001, minCellCount) { if (!"covariates" %in% names(characteristics)) { warning("No characterization output for submitted cohorts") } else if (dplyr::pull(dplyr::count(characteristics$covariateRef)) > 0) { characteristics$filteredCovariates <- characteristics$covariates %>% - dplyr::filter(.data$mean >= minCharacterizationMean) %>% dplyr::mutate(databaseId = !!databaseId) %>% dplyr::left_join(counts, by = c("cohortId", "databaseId"),