@@ -244,7 +244,7 @@

 }

 .runDoubletFinder <- function(counts, seuratPcs, seuratRes, formationRate,

-                              seuratNfeatures, verbose = FALSE,

+                              seuratNfeatures, sct = FALSE, verbose = FALSE,

                               nCores = NULL, seed = 12345) {

   ## Convert to sparse matrix if not already in that format

@@ -285,7 +285,7 @@

   )

   invisible(sweepResListSeurat <- .paramSweep(seurat,

                                               PCs = seuratPcs,

-                                              sct = FALSE,

+                                              sct = sct,

                                               num.cores = nCores,

                                               verbose = verbose,

                                               seed = seed

@@ -306,7 +306,7 @@

                               pK = pkOptimal,

                               nExp = nExpPoi,

                               reuse.pANN = FALSE,

-                              sct = FALSE,

+                              sct = sct,

                               verbose = FALSE

   )

   names([email protected])[6] <- "doubletFinderAnnScore"

@@ -331,6 +331,7 @@

 #' @param seuratRes Numeric vector. The resolution parameter used in Seurat,

 #' which adjusts the number of clusters determined via the algorithm. Default 

 #' \code{1.5}.

+#' @param sct Whether or not to use SCT. Default \code{FALSE}.

 #' @param formationRate Doublet formation rate used within algorithm. Default 

 #' \code{0.075}.

 #' @param nCores Number of cores used for running the function. Default 

@@ -355,6 +356,7 @@ runDoubletFinder <- function(inSCE,

                              seuratNfeatures = 2000,

                              seuratPcs = seq(15),

                              seuratRes = 1.5,

+                             sct = FALSE,

                              formationRate = 0.075,

                              nCores = NULL,

                              verbose = FALSE) {

@@ -405,6 +407,7 @@ runDoubletFinder <- function(inSCE,

           seuratRes = res,

           seuratNfeatures = seuratNfeatures,

           formationRate = formationRate,

+          sct = sct,

           nCores = nCores,

           verbose = verbose,

           seed = seed

@@ -86,7 +86,7 @@ runCellQC <- function(inSCE,

         mitoRef = mitoRef,

         mitoIDType = mitoIDType,

         mitoPrefix = mitoPrefix,

-        mitoID = mitoID,

+        mitoID = list(mitoID),

         mitoGeneLocation = mitoGeneLocation,

         paramsList[["QCMetrics"]]))

   }

@@ -147,6 +147,7 @@ SCANORAMA

 SCDS

 SCE

 SCEsetObject

+SCT

 SCTK

 SCTK's

 SCTransform

@@ -267,7 +268,6 @@ colorBy

 colorScheme

 combineSCE

 compbiomed

-complexed

 computating

 computeHeatmap

 conda

@@ -2025,7 +2025,7 @@ shinyServer(function(input, output, session) {

       soupXParams[["cluster"]] <- NULL

     }

     # add to master params list

-    paramsList[["decontX"]] = soupXParams

+    paramsList[["soupX"]] = soupXParams

     return(paramsList)

   }

@@ -12,6 +12,7 @@ runDoubletFinder(

   seuratNfeatures = 2000,

   seuratPcs = seq(15),

   seuratRes = 1.5,

+  sct = FALSE,

   formationRate = 0.075,

   nCores = NULL,

   verbose = FALSE

@@ -39,6 +40,8 @@ determine number of clusters. Default \code{1:15}.}

 which adjusts the number of clusters determined via the algorithm. Default 

 \code{1.5}.}

+\item{sct}{Whether or not to use SCT. Default \code{FALSE}.}

+

 \item{formationRate}{Doublet formation rate used within algorithm. Default 

 \code{0.075}.}