@@ -215,9 +215,9 @@

 }

 #' Combine a list of SingleCellExperiment objects as one SingleCellExperiment object

-#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects. 

-#' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format. 

-#' It does not support combining SCE with assay in delayedArray format. 

+#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects.

+#' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format.

+#' It does not support combining SCE with assay in delayedArray format.

 #' @param by.r Specifications of the columns used for merging rowData. See 'Details'.

 #' @param by.c Specifications of the columns used for merging colData. See 'Details'.

 #' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.

@@ -228,6 +228,9 @@

 #' @export

 combineSCE <- function(sceList, by.r, by.c, combined){

+  if(length(sceList) == 1){

+    return(sceList[[1]])

+  }

   ##  rowData

   newFeList <- .mergeRowDataSCE(sceList, by.r)

   ## colData

@@ -6,8 +6,8 @@

 #' @param useAssay character. A string specifying which assay to use for the

 #' MAST calculations. Default \code{"logcounts"}.

 #' @param method A single character for specific differential expression

-#' analysis method. Choose from \code{'MAST'}, \code{'DESeq2'}, \code{'Limma'},

-#' and \code{'wilcox'}. Default \code{"wilcox"}.

+#' analysis method. Choose from \code{'wilcox'}, \code{'MAST'}, \code{'DESeq2'},

+#' \code{'Limma'}, and \code{'ANOVA'}. Default \code{"wilcox"}.

 #' @param cluster One single character to specify a column in

 #' \code{colData(inSCE)} for the clustering label. Alternatively, a vector or

 #' a factor is also acceptable. Default \code{"cluster"}.

@@ -33,7 +33,8 @@

 #' @export

 #' @author Yichen Wang

 findMarkerDiffExp <- function(inSCE, useAssay = 'logcounts',

-                              method = c('wilcox', 'MAST', "DESeq2", "Limma"),

+                              method = c('wilcox', 'MAST', "DESeq2", "Limma",

+                                         "ANOVA"),

                               cluster = 'cluster', covariates = NULL,

                               log2fcThreshold = 0.25, fdrThreshold = 0.05,

                               minClustExprPerc = 0.6, maxCtrlExprPerc = 0.4,

@@ -24,7 +24,7 @@ importMultipleSources <- function(allImportEntries, delayedArray = FALSE) {

           delayedArray = delayedArray

         )

       }

-      

+

     } else if (entry$type == "cellRanger3") {

       if (is.null(entry$params$cellRangerDirs)) {

         newSce <- importCellRangerV3Sample(

@@ -93,11 +93,10 @@ importMultipleSources <- function(allImportEntries, delayedArray = FALSE) {

           SummarizedExperiment::assay(newSce, assay) <- DelayedArray::DelayedArray(SummarizedExperiment::assay(newSce, assay))

         }

       }

-      

+

     }

     sceObjs = c(sceObjs, list(newSce))

   }

-  

   return(combineSCE(sceList = sceObjs,

                     by.r = Reduce(base::intersect, lapply(sceObjs, function(x) { colnames(rowData(x))})),

                     by.c = Reduce(base::intersect, lapply(sceObjs, function(x) { colnames(colData(x))})),

@@ -201,7 +201,7 @@ shinyServer(function(input, output, session) {

           }

       }

     }

-    

+

     output[[inputId]] <- renderUI({

       selectInput(

         inputId = inputId,

@@ -221,11 +221,23 @@ shinyServer(function(input, output, session) {

     updateSelectInputTag(session, "clustScranSNNMat", label = "Select Input Matrix:",

                          choices = expDataNames(vals$counts),

                          recommended = "redDims", redDims = TRUE)

-    updateSelectInputTag(session, "deAssay", recommended = c("normalized", "scaled"))

-    updateSelectInputTag(session, "fmAssay", recommended = c("normalized", "scaled"))

+    if (is.null(input$deMethod)) {

+      updateSelectInputTag(session, "deAssay", recommended = c("normalized"))

+    } else if (input$deMethod == "DESeq2") {

+      updateSelectInputTag(session, "deAssay", recommended = c("raw"))

+    } else {

+      updateSelectInputTag(session, "deAssay", recommended = c("normalized"))

+    }

+    if (is.null(input$fmMethod)) {

+      updateSelectInputTag(session, "fmAssay", recommended = c("normalized"))

+    } else if (input$fmMethod == "DESeq2") {

+      updateSelectInputTag(session, "fmAssay", recommended = c("raw"))

+    } else {

+      updateSelectInputTag(session, "fmAssay", recommended = c("normalized"))

+    }

     updateSelectInputTag(session, "fmHMAssay", choices = currassays, selected = input$fmAssay)

     updateSelectInputTag(session, "pathwayAssay", recommended = c("normalized", "scaled"))

-    

+

     #modifyAssaySelect conditions

     if(input$assayModifyAction == "log" || input$assayModifyAction == "log1p"){

       updateSelectInputTag(session, "modifyAssaySelect", recommended = c("raw", "normalized"))

@@ -233,9 +245,9 @@ shinyServer(function(input, output, session) {

     else if(input$assayModifyAction == "z.score"){

       updateSelectInputTag(session, "modifyAssaySelect", recommended = "normalized")

     }

-    

+

     updateSelectInputTag(session, "normalizeAssaySelect", label = "Select assay to normalize:", recommended = "raw")

-    

+

     updateSelectInputTag(session, "seuratSelectNormalizationAssay", choices = currassays, showTags = FALSE)

     updateSelectInputTag(session, "assaySelectFS_Norm", recommended = c("normalized", "scaled"))

     updateSelectInputTag(session, "filterAssaySelect", choices = currassays)

@@ -272,7 +284,7 @@ shinyServer(function(input, output, session) {

                          choices = assayNames(vals$counts),

                          recommended = bc.recommended)

   }

-  

+

   observeEvent(vals$counts, {

     # vals$counts

@@ -843,7 +855,6 @@ shinyServer(function(input, output, session) {

       } else {

         vals$original <- sceObj

       }

-

       # clear table and empty reactive

       for (entry in allImportEntries$samples) {

         removeUI(selector = paste0("#", entry$id))

@@ -851,20 +862,21 @@ shinyServer(function(input, output, session) {

       allImportEntries$samples <- list()

       # Add sample variable if it was not included

-      if(is.null(colData(vals$original)$sample)) {

+      if (!"sample" %in% names(colData(vals$original)) &&

+          !"Sample" %in% names(colData(vals$original))) {

         colData(vals$original)$sample = "sample"

       }

       if (!is.null(vals$original)) {

         vals$counts <- vals$original

-

         #store assayType information in the metadata

-        vals$counts <- expSetDataTag(

-          inSCE = vals$counts,

-          assayType = "raw",

-          assays = assayNames(vals$counts),

-          append = FALSE)

-

+        if (!"assayType" %in% names(metadata(vals$counts))) {

+          vals$counts <- expSetDataTag(

+            inSCE = vals$counts,

+            assayType = "raw",

+            assays = assayNames(vals$counts),

+            append = FALSE)

+        }

         # ToDo: Remove these automatic updates and replace with

         # observeEvents functions that activate upon the tab selection

         updateColDataNames()

@@ -1263,11 +1275,11 @@ shinyServer(function(input, output, session) {

                                  collectionName = qcCollName,

                                  useAssay = input$qcAssaySelect,

                                  paramsList = paramsList)

-        vals$counts <- expSetDataTag(

-          inSCE = vals$counts,

-          assayType = "raw",

-          assays = assayNames(vals$counts),

-          append = FALSE)

+        #vals$counts <- expSetDataTag(

+        #  inSCE = vals$counts,

+        #  assayType = "raw",

+        #  assays = assayNames(vals$counts),

+        #  append = FALSE)

         # redDimList <- strsplit(reducedDimNames(vals$counts), " ")

         # run getUMAP

         message(paste0(date(), " ... Running 'UMAP'"))

@@ -3005,7 +3017,8 @@ shinyServer(function(input, output, session) {

                                    nStart = input$clustKMeansNStart,

                                    algorithm = algo,

                                    clusterName = saveClusterName)

-          updateSelectInput(session, "clustVisReddim", input$clustKMeansReddim)

+          updateSelectInput(session, "clustVisReddim",

+                            selected = input$clustKMeansReddim)

         } else if (input$clustAlgo %in% seq(10, 12)) {

           # Seurat

           if(input$clustSeuratReddim == ""){

@@ -3045,7 +3058,8 @@ shinyServer(function(input, output, session) {

                                             algorithm = algo,

                                             groupSingletons = input$clustSeuratGrpSgltn,

                                             resolution = input$clustSeuratRes)

-          updateSelectInput(session, "clustVisReddim", input$clustSeuratReddim)

+          updateSelectInput(session, "clustVisReddim",

+                            selected = input$clustSeuratReddim)

         }

         updateColDataNames()

         clustResults$names <- c(clustResults$names, saveClusterName)

@@ -3652,7 +3666,7 @@ shinyServer(function(input, output, session) {

       }else if(input$TypeSelect_Colorby == "Expression Assays"){

         a <- plotSCEDimReduceFeatures(vals$counts, feature = input$GeneSelect_Assays_Colorby,

                                       reducedDimName = input$QuickAccess, useAssay = input$AdvancedMethodSelect_Colorby,

-                                      xlab = xname, ylab = yname, legendTitle = legendname, title = input$adjustitle,

+                                      xlab = xname, ylab = yname, legendTitle = legendname, title = input$adjusttitle,

                                       groupBy = pltVars$groupby, bin = pltVars$bin, transparency = input$adjustalpha,

                                       colorLow = input$lowColor, colorMid = input$midColor, colorHigh = input$highColor,

                                       dotSize = input$adjustsize, combinePlot = "none", axisSize = input$adjustaxissize,

@@ -5080,51 +5094,64 @@ shinyServer(function(input, output, session) {

   #-----------------------------------------------------------------------------

   # Page 5.1: Differential Expression ####

   #-----------------------------------------------------------------------------

-  ## DE - Thresholding Vis ####

+  observeEvent(input$deMethod, {

+    if (!is.null(vals$counts)) {

+      if (is.null(input$deMethod)) {

+        updateSelectInputTag(session, "deAssay", recommended = c("normalized"))

+      } else if (input$deMethod == "DESeq2") {

+        updateSelectInputTag(session, "deAssay", recommended = c("raw"))

+      } else {

+        updateSelectInputTag(session, "deAssay", recommended = c("normalized"))

+      }

+    }

+  })

+  ## DE - Thresholding Vis ####

   observeEvent(input$deViewThresh, {

     if (!is.null(vals$counts) &&

         !is.null(input$deAssay)) {

       shinyjs::showElement(id= "deThreshpanel")

-    }

-  })

-

-  # Threshold adapting plot

-  observeEvent(input$deAssay, {

-    if(!is.null(vals$counts)){

-      # MAST style sanity check for whether logged or not

-      x <- expData(vals$counts, input$deAssay)

-      if (!all(floor(x) == x, na.rm = TRUE) & max(x, na.rm = TRUE) <

-          100) {

-        output$deSanityWarnThresh <- renderText("")

-        isLogged <- TRUE

-      } else {

-        output$deSanityWarnThresh <- renderText("Selected assay seems not logged (MAST style sanity check). Forcing to plot by automatically applying log-transformation. ")

-        isLogged <- FALSE

-      }

-      thres.grob <- plotMASTThresholdGenes(inSCE = vals$counts,

-                                           useAssay = input$deAssay,

-                                           check_sanity = FALSE,

-                                           isLogged = isLogged,

-                                           doPlot = FALSE)

-      nSub <- tail(strsplit(thres.grob$childrenOrder, split = '-'),

-                   n = 1)[[1]][3]

-      plotHeight <- ceiling(as.numeric(nSub) / 4) * 240

-

-      output$deThreshPlotDiv <- renderUI({

-        div(

-          style = paste0("height: ", plotHeight, "px;"),

-          plotOutput("deThreshplot"))

+      withProgress(message = "Plotting thresholding...", max = 1, value = 1, {

+        withBusyIndicatorServer("deViewThresh", {

+          # MAST style sanity check for whether logged or not

+          x <- expData(vals$counts, input$deAssay)

+          if (!all(floor(x) == x, na.rm = TRUE) & max(x, na.rm = TRUE) <

+              100) {

+            output$deSanityWarnThresh <- renderText("")

+            isLogged <- TRUE

+          } else {

+            output$deSanityWarnThresh <- renderText("Selected assay seems not logged (MAST style sanity check). Forcing to plot by automatically applying log-transformation. ")

+            isLogged <- FALSE

+          }

+          suppressMessages({

+            thres.grob <- plotMASTThresholdGenes(inSCE = vals$counts,

+                                                 useAssay = input$deAssay,

+                                                 check_sanity = FALSE,

+                                                 isLogged = isLogged,

+                                                 doPlot = FALSE)

+          })

+          nSub <- tail(strsplit(thres.grob$childrenOrder, split = '-'),

+                       n = 1)[[1]][3]

+          plotHeight <- ceiling(as.numeric(nSub) / 4) * 240

+

+          output$deThreshPlotDiv <- renderUI({

+            div(

+              style = paste0("height: ", plotHeight, "px;"),

+              plotOutput("deThreshplot"))

+          })

+          output$deThreshplot <- renderPlot({

+            grid.draw(thres.grob)

+          }, height = plotHeight)

+          updateActionButton(session, "deViewThresh", "Refresh")

+        })

       })

-      output$deThreshplot <- renderPlot({

-        grid.draw(thres.grob)

-      }, height = plotHeight)

     }

   })

   observeEvent(input$deHideThresh, {

     shinyjs::hideElement(id= "deThreshpanel")

+    updateActionButton(session, "deViewThresh", "View Thresholding")

   })

   ## DE - condition determination method1 ####

@@ -5443,7 +5470,8 @@ shinyServer(function(input, output, session) {

   # Data table

   output$deResult <- DT::renderDataTable({

-    if(!is.null(input$deResSel)){

+    if(!is.null(input$deResSel) &&

+       !is.null(vals$counts)){

       metadata(vals$counts)$diffExp[[input$deResSel]]$result

     }

   }, filter = 'top')

@@ -5476,7 +5504,8 @@ shinyServer(function(input, output, session) {

   observeEvent(input$dePlotVio, {

     if(!is.null(input$deResSel) &&

-       !input$deResSel == ""){

+       !input$deResSel == "" &&

+       !is.null(vals$counts)){

       sce <- vals$counts

       useResult <- input$deResSel

       nrow <- input$deVioNRow

@@ -5514,7 +5543,8 @@ shinyServer(function(input, output, session) {

   observeEvent(input$dePlotReg, {

     if(!is.null(input$deResSel) &&

-       !input$deResSel == ""){

+       !input$deResSel == "" &&

+       !is.null(vals$counts)){

       sce <- vals$counts

       useResult <- input$deResSel

       nrow <- input$deRegNRow

@@ -5584,6 +5614,17 @@ shinyServer(function(input, output, session) {

   #-----------------------------------------------------------------------------

   # Page 5.2: Find Marker ####

   #-----------------------------------------------------------------------------

+  observeEvent(input$fmMethod, {

+    if (!is.null(vals$counts)) {

+      if (is.null(input$fmMethod)) {

+        updateSelectInputTag(session, "fmAssay", recommended = c("normalized"))

+      } else if (input$fmMethod == "DESeq2") {

+        updateSelectInputTag(session, "fmAssay", recommended = c("raw"))

+      } else {

+        updateSelectInputTag(session, "fmAssay", recommended = c("normalized"))

+      }

+    }

+  })

   # findMarker RUN ####

   observeEvent(input$runFM, {

     if (is.null(vals$counts)){

@@ -5604,6 +5645,7 @@ shinyServer(function(input, output, session) {

                                          fdrThreshold = input$fmFDR)

         shinyalert::shinyalert("Success", "Find Marker completed.",

                                "success")

+        updateFMPlot()

       })

     }

   })

@@ -5615,7 +5657,7 @@ shinyServer(function(input, output, session) {

       fullTable[,5] <- as.factor(fullTable[,5])

       fullTable

     }

-  }, filter = "top")

+  }, filter = "top", options = list(scrollX = TRUE))

   observe({

     if (!is.null(vals$counts) &&

@@ -5646,51 +5688,53 @@ shinyServer(function(input, output, session) {

     }

   })

-  # output$fmHMAssayUI <- renderUI({

-  #   if(!is.null(vals$counts)){

-  #     allAssay <- assayNames(vals$counts)

-  #     selectInput('fmHMAssay', "Assay to plot", allAssay,

-  #                 selected = input$fmAssay)

-  #   }

-  # })

-

   observeEvent(input$plotFM, {

+    updateFMPlot()

+  })

+

+  updateFMPlot <- function() {

     if(!is.null(vals$counts) &&

        'findMarker' %in% names(metadata(vals$counts))){

       withBusyIndicatorServer("plotFM", {

-        if(isTRUE(input$fmUseTopN)

-           && is.na(input$fmTopN)){

-          stop("Top N marker must be a numeric non-empty value")

-        }

-        if(is.na(input$fmHMFC)){

-          stop("Log2FC must be a numeric non-empty value!")

-        }

-        if(is.na(input$fmHMFDR)){

-          stop("FDR must be a numeric non-empty value!")

-        }

-      inSCE <- vals$counts

-      orderBy <- input$fmHMOrder

-      log2fcThreshold <- input$fmHMFC

-      fdrThreshold <- input$fmHMFDR

-      decreasing <- input$fmHMdec

-      rowDataName <- input$fmHMrowData

-      colDataName <- input$fmHMcolData

-      if(!isTRUE(input$fmUseTopN)) {

-        topN <- NULL

-      } else {

-        topN <- input$fmTopN

-      }

-      # Take value before rendering plot, so that the plot doesnt auto re-render

-      # while we tweak the parameter

-      output$fmHeatmap <- renderPlot({

-        plotMarkerDiffExp(inSCE = inSCE, orderBy = orderBy,

-                          log2fcThreshold = log2fcThreshold, topN = topN,

-                          fdrThreshold = fdrThreshold, decreasing = decreasing,

-                          rowDataName = rowDataName, colDataName = colDataName)

-      })

+        withProgress(message = "Updating marker heatmap...", max = 1, value = 1, {

+          if(isTRUE(input$fmUseTopN)

+             && is.na(input$fmTopN)){

+            stop("Top N marker must be a numeric non-empty value")

+          }

+          if(is.na(input$fmHMFC)){

+            stop("Log2FC must be a numeric non-empty value!")

+          }

+          if(is.na(input$fmHMFDR)){

+            stop("FDR must be a numeric non-empty value!")

+          }

+          inSCE <- vals$counts

+          orderBy <- input$fmHMOrder

+          log2fcThreshold <- input$fmHMFC

+          fdrThreshold <- input$fmHMFDR

+          decreasing <- input$fmHMdec

+          rowDataName <- input$fmHMrowData

+          colDataName <- input$fmHMcolData

+          if(!isTRUE(input$fmUseTopN)) {

+            topN <- NULL

+          } else {

+            topN <- input$fmTopN

+          }

+          # Take value before rendering plot, so that the plot doesn't auto

+          # re-render while we tweak the parameter

+          output$fmHeatmap <- renderPlot({

+            plotMarkerDiffExp(inSCE = inSCE,

+                              orderBy = orderBy,

+                              log2fcThreshold = log2fcThreshold,

+                              topN = topN,

+                              fdrThreshold = fdrThreshold,

+                              decreasing = decreasing,

+                              rowDataName = rowDataName,

+                              colDataName = colDataName)

+          })

+        })

       })

     }

-  })

+  }

   #-----------------------------------------------------------------------------

   # Page 6: Pathway Activity Analysis

@@ -7820,8 +7864,9 @@ shinyServer(function(input, output, session) {

       }

       if (input$exportChoice == "rds") {

-        filename = paste("SCE-", Sys.Date(), ".rds", sep = "")

-        saveRDS(vals$counts, paste(exportPath, "/", filename, sep = ""))

+        filename = paste0("SCE_", strftime(Sys.time(), format = "%y%m%d_%H%m"),

+                         ".rds")

+        saveRDS(vals$counts, paste0(exportPath, "/", filename))

       } else if (input$exportChoice == "annData") {

         exportassay <- input$exportAssay

         compression <- input$compression

@@ -7831,7 +7876,9 @@ shinyServer(function(input, output, session) {

         exportSCEtoAnnData(sce=vals$counts,

                            useAssay = exportassay,

                            outputDir=exportPath,

-                           prefix = paste("SCE-", Sys.Date(),sep = ""),

+                           prefix = paste0("SCE-",

+                                           strftime(Sys.time(),

+                                                    format = "%y%m%d_%H%m")),

                            overwrite=overwrite,

                            compression = compression,

                            compressionOpts = compressionOpts,

@@ -7843,7 +7890,9 @@ shinyServer(function(input, output, session) {

                             outputDir=exportPath,

                             overwrite=overwrite,

                             gzipped=gzipped,

-                            sample = paste("SCE-", Sys.Date(),sep = ""))

+                            sample = paste0("SCE-",

+                                            strftime(Sys.time(),

+                                                     format = "%y%m%d_%H%m")))

       }

     })

   })

@@ -8,18 +8,15 @@ shinyPanelDiffex <- fluidPage(

       panel(

         style = "margin:2px;",

         h3("Method and Matrix"),

-        p("For 'MAST', 'Limma' and 'ANOVA', log-transformed count matrix is preferred; for 'DESeq2', count matrix is preferred.",

-          style = "color:grey;"),

         fluidRow(

           column(

             4,

             selectInput('deMethod', "Choose analysis method",

-                        c('MAST', 'DESeq2', 'Limma', 'ANOVA'))

+                        c('wilcox', 'MAST', 'DESeq2', 'Limma', 'ANOVA'))

           ),

           column(

             4,

             uiOutput("deAssay")

-            #selectInput("deAssay", "Select Assay:", currassays)

           )

         ),

         useShinyjs(),

@@ -142,7 +139,7 @@ shinyPanelDiffex <- fluidPage(

             width = 3,

             numericInput("deFCThresh",

                          "Output Log2FC Absolute value greater than:",

-                         min = 0, step = 0.05, value = 1)

+                         min = 0, step = 0.05, value = 0.5)

           ),

           column(

             width = 3,

@@ -6,12 +6,9 @@ shinyPanelfindMarker <- fluidPage(

            "(help)", target = "_blank"),

     sidebarLayout(

       sidebarPanel(

-        p("For 'MAST' and 'Limma', log-transformed count matrix is preferred; for 'DESeq2', count matrix is preferred.",

-          style = "color:grey;"),

-        uiOutput('fmAssay'),

-        #selectInput('fmAssay', "Select Assay", currassays),

         selectInput('fmMethod', "Select Differential Expression Method",

-                    c("MAST", "DESeq2", "Limma")),

+                    c("wilcox", "MAST", "DESeq2", "Limma", "ANOVA")),

+        uiOutput('fmAssay'),

         selectInput("fmCluster", "Cluster Annotation", clusterChoice),

         numericInput("fmLogFC", "Log2FC greater than",

                      value = 0.25, min = 0, step = 0.05),

@@ -7,8 +7,8 @@

 combineSCE(sceList, by.r, by.c, combined)

 }

 \arguments{

-\item{sceList}{A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects. 

-Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format. 

+\item{sceList}{A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects.

+Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format.

 It does not support combining SCE with assay in delayedArray format.}

 \item{by.r}{Specifications of the columns used for merging rowData. See 'Details'.}

@@ -10,7 +10,7 @@ on each cluster against all the others.}

 findMarkerDiffExp(

   inSCE,

   useAssay = "logcounts",

-  method = c("wilcox", "MAST", "DESeq2", "Limma"),

+  method = c("wilcox", "MAST", "DESeq2", "Limma", "ANOVA"),

   cluster = "cluster",

   covariates = NULL,

   log2fcThreshold = 0.25,

@@ -27,8 +27,8 @@ findMarkerDiffExp(

 MAST calculations. Default \code{"logcounts"}.}

 \item{method}{A single character for specific differential expression

-analysis method. Choose from \code{'MAST'}, \code{'DESeq2'}, \code{'Limma'},

-and \code{'wilcox'}. Default \code{"wilcox"}.}

+analysis method. Choose from \code{'wilcox'}, \code{'MAST'}, \code{'DESeq2'},

+\code{'Limma'}, and \code{'ANOVA'}. Default \code{"wilcox"}.}

 \item{cluster}{One single character to specify a column in

 \code{colData(inSCE)} for the clustering label. Alternatively, a vector or