Minimum mean for covariates included in feature extraction and remove…

…d filter
OHDSI · Aug 7, 2024 · e4c912c · e4c912c
1 parent 9900a09
commit e4c912c
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Showing 3 changed files with 7 additions and 7 deletions.
diff --git 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
@@ -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
@@ -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"),