@@ -17,3 +17,4 @@ exec/png

 ^\.github$

 ^vignettes/articles/*

 ^images

+.dockerignore

\ No newline at end of file

new file mode 100644

@@ -0,0 +1,7 @@

+.RData

+.Rhistory

+.git

+.gitignore

+manifest.json

+rsconnect/

+.Rproj.user

\ No newline at end of file

@@ -118,8 +118,9 @@ Imports:

     scuttle,

     utils,

     stats,

-    zellkonverter

-RoxygenNote: 7.3.1

+    zellkonverter,

+    tidyr

+RoxygenNote: 7.3.2

 Suggests:

     testthat,

     Rsubread,

@@ -131,6 +131,13 @@ computeHeatmap <- function(inSCE,

     features[[i]] <- .convertToHyphen(features[[i]])

   }

+  ## temp fix

+  # make sure the cell names are consistent

+  # UPDATE THIS IN .convertSCEToSeurat function eventually

+  rownames(object@[email protected]) <- 

+    unlist(.convertToHyphen(rownames(object@[email protected])))

+  ## 

+  

   object <- Seurat::ScaleData(object, features = features.all)

   # get assay data with only selected features (all dims) and

@@ -342,6 +342,7 @@

 #' @seealso \code{\link{runCellQC}}, \code{\link{plotDoubletFinderResults}}

 #' @examples

 #' data(scExample, package = "singleCellTK")

+#' options(future.globals.maxSize = 786432000)

 #' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

 #' sce <- runDoubletFinder(sce)

 #' @export

@@ -26,7 +26,7 @@

 #' @title Identify empty droplets using \link[DropletUtils]{emptyDrops}.

 #' @description Run \link[DropletUtils]{emptyDrops} on the count matrix in the

-#' provided \\linkS4class{SingleCellExperiment} object.

+#' provided \linkS4class{SingleCellExperiment} object.

 #' Distinguish between droplets containing cells and ambient RNA in a

 #' droplet-based single-cell RNA sequencing experiment.

 #' @param inSCE A \linkS4class{SingleCellExperiment} object. Must contain a raw 

@@ -852,11 +852,19 @@ plotSCEScatter <- function(inSCE,

                       vcolor = "red",

                       vsize = 1,

                       vlinetype = 1) {

+  

+  mult_modules <- FALSE

+  

   if (is.null(groupBy)) {

-    groupBy <- rep("Sample", length(y))

+    if (length(colnames(y)) > 1){

+      mult_modules <- TRUE

+      groupBy <- rep(colnames(y), each = dim(y)[1])

+      y <- tidyr::pivot_longer(as.data.frame(y), cols = 1:dim(y)[2], cols_vary = "slowest")$value#

+    }else{

+      groupBy <- rep("Sample", length(y))

+    }

   }

-  

   if(!is.factor(groupBy)){

     if(is.null(plotOrder)){

       plotOrder = unique(groupBy)

@@ -920,6 +928,10 @@ plotSCEScatter <- function(inSCE,

                             axis.title.x = ggplot2::element_blank())

   }

+  if (mult_modules){

+    p <- p + xlab("Modules")

+  }

+  

   if (gridLine == TRUE){

     p <- p + ggplot2::theme(panel.grid.major.y = ggplot2::element_line("grey"))

   }

@@ -1417,9 +1429,9 @@ plotSCEViolinAssayData <- function(inSCE,

 #' @param feature Desired name of feature stored in assay of SingleCellExperiment

 #'  object. Only used when "assays" slotName is selected. Default NULL.

 #' @param sample Character vector. Indicates which sample each cell belongs to.

-#' @param dimension Desired dimension stored in the specified reducedDims.

-#'  Either an integer which indicates the column or a character vector specifies

-#'  column name. By default, the 1st dimension/column will be used.

+#' @param dimension Desired dimension(s) stored in the specified reducedDims.

+#'  Either an integer which indicates the column(s) or a character vector specifies

+#'  column name(s). By default, the 1st dimension/column will be used.

 #'  Only used when "reducedDims" slotName is selected. Default NULL.

 #' @param groupBy Groupings for each numeric value. A user may input a vector

 #' equal length to the number of the samples in the SingleCellExperiment

@@ -1568,7 +1580,11 @@ plotSCEViolin <- function(inSCE,

   samples <- unique(sample)

   plotlist <- lapply(samples, function(x) {

     sampleInd <- which(sample == x)

-    countSub <- counts[sampleInd]

+    if (length(colnames(counts)) > 1){

+      countSub <- counts[sampleInd,]

+    }else{

+      countSub <- counts[sampleInd]

+    }

     if(!is.null(groupBy)){

       groupbySub <- groupBy[sampleInd]

     }else{

@@ -191,18 +191,18 @@ discreteColorPalette <- function(n, palette = c("random", "ggplot", "celda"),

 #' Adds '-1', '-2', ... '-i' to multiple duplicated rownames, and in place

 #' replace the unique rownames, store unique rownames in \code{rowData}, or

 #' return the unique rownames as character vecetor.

-#' @param x A matrix like or /linkS4class{SingleCellExperiment} object, on which

+#' @param x A matrix like or \linkS4class{SingleCellExperiment} object, on which

 #' we can apply \code{rownames()} to and has duplicated rownames.

 #' @param as.rowData Only applicable when \code{x} is a

-#' /linkS4class{SingleCellExperiment} object. When set to \code{TRUE}, will

+#' \linkS4class{SingleCellExperiment} object. When set to \code{TRUE}, will

 #' insert a new column called \code{"rownames.uniq"} to \code{rowData(x)}, with

 #' the deduplicated rownames.

 #' @param return.list When set to \code{TRUE}, will return a character vector

 #' of the deduplicated rownames.

 #' @export

-#' @return By default, a matrix or /linkS4class{SingleCellExperiment} object

+#' @return By default, a matrix or \linkS4class{SingleCellExperiment} object

 #' with rownames deduplicated.

-#' When \code{x} is a /linkS4class{SingleCellExperiment} and \code{as.rowData}

+#' When \code{x} is a \linkS4class{SingleCellExperiment} and \code{as.rowData}

 #' is set to \code{TRUE}, will return \code{x} with \code{rowData} updated.

 #' When \code{return.list} is set to \code{TRUE}, will return a character vector

 #' with the deduplicated rownames.

@@ -12,7 +12,7 @@

 #' @param ylab The y-axis label

 #' @param colorLow The color to be used for lowest value of mean expression

 #' @param colorHigh The color to be used for highest value of mean expression

-#' @param scale Option to scale the data. Default: /code{FALSE}. Selected assay will not be scaled. 

+#' @param scale Option to scale the data. Default: \code{FALSE}. Selected assay will not be scaled. 

 #' @return A ggplot of the bubble plot.

 #' @importFrom rlang .data

 #' @importFrom reshape2 melt

@@ -670,7 +670,7 @@ integrated = integrated[:, orderIdx]

 #' variable genes identification. Default \code{"counts"}.

 #' @param kmeansK An integer vector. Indicating the kmeans' K-value for each

 #' batch (i.e. how many subclusters in each batch should exist), in order to

-#' construct pseudo-replicates. The length of code{kmeansK} needs to be the same

+#' construct pseudo-replicates. The length of \code{kmeansK} needs to be the same

 #' as the number of batches. Default \code{NULL}, and this value will be

 #' auto-detected by default, depending on \code{cellType}.

 #' @param cellType A single character. A string indicating a field in

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

 #' @param featureNames A string or vector of strings with each gene to aggregate.

 #' @param displayName A string that is the name of the column used for genes.

 #' @param groupNames The name of a colData entry that can be used as groupNames.

-#' @param scale Option to scale the data. Default: /code{FALSE}. Selected assay will not be scaled. 

+#' @param scale Option to scale the data. Default: \code{FALSE}. Selected assay will not be scaled. 

 #' @return A dataframe with mean expression and percent of cells in cluster that 

 #' express for each cluster.

 #' @examples

@@ -76,7 +76,7 @@ runDimReduce <- function(inSCE,

                        seed = seed, ...)

   } else if (method == "scaterUMAP") {

     inSCE <- runUMAP(inSCE = inSCE, useAssay = useAssay, useAltExp = useAltExp,

-                     useReducedDim = useReducedDim, initialDims = 25,

+                     useReducedDim = useReducedDim,

                      useFeatureSubset = useFeatureSubset, scale = scale,

                      reducedDimName = reducedDimName, seed = seed, ...)

   } else if (method == "scanpyPCA"){

@@ -30,6 +30,16 @@

     return(componentNames)

   }

+#' .getSeuratObject

+#' Retrieves the Seurat object stored in the input SCE, if exists

+#' @param inSCE (sce) object containing the Seurat data, located

+#' in inSCE\@\metadata$seurat$obj

+#' @return the Seurat object if it exists

+#' @noRd

+.getSeuratObject <- function(inSCE) { 

+  return(metadata(inSCE)$seurat$obj)

+}

+

 #' .addSeuratToMetaDataSCE

 #' Adds the input seurat object to the metadata slot of the input sce object

 #' (after removing the data matrices)

@@ -44,25 +54,38 @@

   seurat.version <- .getSeuratObjectMajorVersion(seuratObject)

   if(seurat.version >= 5.0){

-    inSCE@metadata$seurat$obj$RNA$"var.features" <-

-      Seurat::VariableFeatures(object = seuratObject)

-    # Determine if slot is called "meta.data" or "meta.features

-    if("meta.data" %in% methods::slotNames(inSCE@metadata$seurat$obj$RNA)) {

-        inSCE@metadata$seurat$obj$RNA$meta.features  <- seuratObject@[email protected]    

-    } else if ("meta.features" %in% methods::slotNames(inSCE@metadata$seurat$obj$RNA)) {

-        inSCE@metadata$seurat$obj$RNA$meta.features  <- seuratObject@[email protected]

-    }

+    seuratObject@assays$RNA@layers$counts <- methods::new("dgCMatrix")

+    seuratObject@assays$RNA@layers$data <- methods::new("dgCMatrix")

+    seuratObject@assays$RNA@layers$scale.data <- methods::new("dgCMatrix")

+    inSCE@metadata$seurat$obj <- seuratObject

+    

+    # add var features if exists

+    #if (!is.null(Seurat::VariableFeatures(seuratObject)) && length(Seurat::VariableFeatures(seuratObject)) > 0) {

+    #  inSCE@metadata$seurat$obj@assays$RNA$"var.features" <-

+    #    Seurat::VariableFeatures(object = seuratObject)

+    #}

-    inSCE@metadata$seurat$obj$meta.data <- [email protected]

+    #inSCE@metadata$seurat$obj@assays$RNA@layers$counts <- methods::new("dgCMatrix")

+    #inSCE@metadata$seurat$obj@assays$RNA@layers$data <- methods::new("dgCMatrix")

+    #inSCE@metadata$seurat$obj@assays$RNA@layers$scale.data <- matrix()

+    

+    # Determine if slot is called "meta.data" or "meta.features"

+      if("meta.data" %in% methods::slotNames(seuratObject@assays$RNA)) {

+         inSCE@metadata$seurat$obj@[email protected]  <- seuratObject@[email protected]    

+      } else if ("meta.features" %in% methods::slotNames(seuratObject@assays$RNA)) {

+         inSCE@metadata$seurat$obj@[email protected]  <- seuratObject@[email protected]

+      }

-    inSCE@metadata$seurat$obj$commands <- seuratObject@commands

+    inSCE@[email protected] <- [email protected]

-    inSCE@metadata$seurat$obj$reductions$pca <- seuratObject@reductions$pca

-    inSCE@metadata$seurat$obj$reductions$ica <- seuratObject@reductions$ica

-    inSCE@metadata$seurat$obj$reductions$tsne <- seuratObject@reductions$tsne

-    inSCE@metadata$seurat$obj$reductions$umap <- seuratObject@reductions$umap

+    inSCE@metadata$seurat$obj@commands <- seuratObject@commands

+    inSCE@metadata$seurat$obj@reductions$pca <- seuratObject@reductions$pca

+    inSCE@metadata$seurat$obj@reductions$ica <- seuratObject@reductions$ica

+    inSCE@metadata$seurat$obj@reductions$tsne <- seuratObject@reductions$tsne

+    inSCE@metadata$seurat$obj@reductions$umap <- seuratObject@reductions$umap

+

   }

   else{

     seuratObject@assays$RNA@counts <- methods::new("dgCMatrix")

@@ -541,6 +564,7 @@ runSeuratICA <-

            verbose = FALSE) {

     params <- as.list(environment())

     params$inSCE <- NULL

+    

     if (!isTRUE(scale)) {

       # If not doing a scaling, put useAssay as scaled as RunPCA need it

       seuratObject <-

@@ -618,7 +642,6 @@ runSeuratJackStraw <- function(inSCE,

                                externalReduction = NULL) {

   seuratObject <- convertSCEToSeurat(inSCE, normAssay = useAssay)

   seuratObject <- Seurat::ScaleData(seuratObject)

-

   if (!is.null(externalReduction)) {

     #convert (_) to (-) as required by Seurat

@@ -783,7 +806,7 @@ plotSeuratReduction <-

       if (!is.null([email protected]$seurat_clusters)) {

         Seurat::Idents(seuratObject) <-

           [email protected]$seurat_clusters

-        [email protected] <- data.frame()

+        #[email protected] <- data.frame()

       }

     }

@@ -1065,13 +1088,16 @@ runSeuratUMAP <- function(inSCE,

   seurat.version <- .getSeuratObjectMajorVersion(seuratObject)

   if(seurat.version >= 5.0){

-    if (length(seuratObject@assays$RNA@misc$var.features) > 0) {

-      return(seuratObject@assays$RNA@misc$var.features[seq(numberOfFeatures)])

+    if (length(SeuratObject::Features(seuratObject)) > 0) {

+      return(SeuratObject::Features(seuratObject)[seq(numberOfFeatures)])

     }

+    #if (length(seuratObject@assays$RNA@misc$var.features) > 0) {

+    #  return(seuratObject@assays$RNA@misc$var.features[seq(numberOfFeatures)])

+    #}

   }

   else{

-    if (length(seuratObject@[email protected]) > 0) {

-      return(seuratObject@[email protected][seq(numberOfFeatures)])

+    if (length(seuratObject@[email protected]$var.features) > 0) {

+      return(seuratObject@[email protected]$var.features[seq(numberOfFeatures)])

     }

   }

 }

@@ -1551,46 +1577,57 @@ convertSCEToSeurat <-

     if(seurat.version >= 5.0){

       if (!is.null(inSCE@metadata$seurat$obj)) {

-        if (length(inSCE@metadata$seurat$obj$RNA$"var.features") > 0) {

-          seuratObject@assays$RNA@misc$"var.features" <- 

-            inSCE@metadata$seurat$obj$RNA$"var.features"

+        # what is it looking for here? sequence? idk

+

+        if ((nrow(inSCE@metadata$seurat$obj@assays$RNA) > 0 && ncol(inSCE@metadata$seurat$obj@assays$RNA) > 0) && !is.null(inSCE@metadata$seurat$obj@[email protected]$var.features)) {

+          seuratObject@[email protected]$var.features <- 

+            inSCE@metadata$seurat$obj@[email protected]$var.features

         }

-        if (!is.null(inSCE@metadata$seurat$obj$reductions$pca)) {

+        

+        # if no, then set a new matrix to empty

+        # if (is.null(inSCE@metadata$seurat$obj@[email protected]$var.features)) {

+        #   seuratObject@[email protected]$var.features <- 

+        #     data.frame(matrix(NA, nrow = nrow(inSCE@metadata$seurat$obj@assays$RNA), ncol = ncol(inSCE@metadata$seurat$obj@assays$RNA)))

+        # }

+        

+        if (!is.null(inSCE@metadata$seurat$obj@reductions) && !is.null(inSCE@metadata$seurat$obj@reductions$pca)) {

           seuratObject@reductions$pca <-

-            inSCE@metadata$seurat$obj$reductions$pca

+            inSCE@metadata$seurat$obj@reductions$pca

         }

-        if (!is.null(inSCE@metadata$seurat$obj$RNA$meta.features)) {

+        if ((nrow(inSCE@metadata$seurat$obj@assays$RNA) > 0 && ncol(inSCE@metadata$seurat$obj@assays$RNA) > 0) && !is.null(inSCE@metadata$seurat$obj@[email protected])) {

           seuratObject@[email protected] <-

-            inSCE@metadata$seurat$obj$RNA$meta.features

+            inSCE@metadata$seurat$obj@[email protected]

+          #seuratObject <-

+          #  SeuratObject::AddMetaData(seuratObject, inSCE@metadata$seurat$obj@[email protected])

         }

-        if (!is.null(inSCE@metadata$seurat$obj$reductions$ica)) {

+        if (!is.null(inSCE@metadata$seurat$obj@reductions$ica)) {

           seuratObject@reductions$ica <-

-            inSCE@metadata$seurat$obj$reductions$ica

+            inSCE@metadata$seurat$obj@reductions$ica

         }

-        if (!is.null(inSCE@metadata$seurat$obj$reductions$tsne)) {

+        if (!is.null(inSCE@metadata$seurat$obj@reductions$tsne)) {

           seuratObject@reductions$tsne <-

-            inSCE@metadata$seurat$obj$reductions$tsne

+            inSCE@metadata$seurat$obj@reductions$tsne

         }

-        if (!is.null(inSCE@metadata$seurat$obj$reductions$umap)) {

+        if (!is.null(inSCE@metadata$seurat$obj@reductions$umap)) {

           seuratObject@reductions$umap <-

-            inSCE@metadata$seurat$obj$reductions$umap

+            inSCE@metadata$seurat$obj@reductions$umap

         }

-        if (!is.null(inSCE@metadata$seurat$obj$meta.data)) {

+        if (!is.null(inSCE@[email protected])) {

           #[email protected] <- 

             #inSCE@metadata$seurat$obj$meta.data[match(colnames(seuratObject), rownames(inSCE@metadata$seurat$obj$meta.data)),]

           seuratObject <- 

-            SeuratObject::AddMetaData(seuratObject, inSCE@metadata$seurat$obj$meta.data[match(colnames(seuratObject), rownames(inSCE@metadata$seurat$obj$meta.data)),])

+            SeuratObject::AddMetaData(seuratObject, inSCE@[email protected][match(colnames(seuratObject), rownames(inSCE@[email protected])),])

         }

-        if (!is.null(inSCE@metadata$seurat$obj$commands)) {

-          seuratObject@commands <- inSCE@metadata$seurat$obj$commands

+        if (!is.null(inSCE@metadata$seurat$obj@commands)) {

+          seuratObject@commands <- inSCE@metadata$seurat$obj@commands

         }

       }

     }

     else{

       if (!is.null(inSCE@metadata$seurat$obj)) {

-        if (length(inSCE@metadata$seurat$obj@[email protected]) > 0) {

-          seuratObject@[email protected] <-

-            inSCE@metadata$seurat$obj@[email protected]

+        if (length(inSCE@metadata$seurat$obj@[email protected]$var.features) > 0) {

+          seuratObject@[email protected]$var.features <-

+            inSCE@metadata$seurat$obj@[email protected]$var.features

         }

         if (!is.null(inSCE@metadata$seurat$obj@reductions$pca)) {

           seuratObject@reductions$pca <-

@@ -1613,7 +1650,9 @@ convertSCEToSeurat <-

             inSCE@metadata$seurat$obj@reductions$umap

         }

         if (!is.null(inSCE@[email protected])) {

-          [email protected] <- inSCE@[email protected][match(colnames(seuratObject), rownames(inSCE@[email protected])),]

+          #[email protected] <- inSCE@[email protected][match(colnames(seuratObject), rownames(inSCE@[email protected])),]

+          seuratObject <- 

+            SeuratObject::AddMetaData(seuratObject, inSCE@metadata$seurat$obj$meta.data[match(colnames(seuratObject), rownames(inSCE@metadata$seurat$obj$meta.data)),])

         }

         if (!is.null(inSCE@metadata$seurat$obj@commands)) {

           seuratObject@commands <- inSCE@metadata$seurat$obj@commands

@@ -1624,6 +1663,7 @@ convertSCEToSeurat <-

     if (!is.null(colData(inSCE)) && copyColData) {

       [email protected] <-

         cbind([email protected], colData(inSCE))

+      #seuratObject <- SeuratObject::AddMetaData(seuratObject, colData(inSCE))

     }

     # Set additional reducedDims from inSCE object if required

@@ -1776,16 +1816,16 @@ runSeuratSCTransform <- function(inSCE,

         #inSCE@metadata$seurat$heatmap_pca <- NULL

       }

       if (PCA) {

-        inSCE@metadata$seurat$obj$reductions$pca <- NULL

+        inSCE@metadata$seurat$obj@reductions$pca <- NULL

       }

       if (ICA) {

-        inSCE@metadata$seurat$obj$reductions$ica <- NULL

+        inSCE@metadata$seurat$obj@reductions$ica <- NULL

       }

       if (tSNE) {

-        inSCE@metadata$seurat$obj$reductions$tsne <- NULL

+        inSCE@metadata$seurat$obj@reductions$tsne <- NULL

       }

       if (UMAP) {

-        inSCE@metadata$seurat$obj$reductions$umap <- NULL

+        inSCE@metadata$seurat$obj@reductions$umap <- NULL

       }

       if (clusters) {

         inSCE@metadata$seurat$obj$meta.data$seurat_clusters <- NULL

@@ -1793,10 +1833,19 @@ runSeuratSCTransform <- function(inSCE,

     }

     if(methods::is(inSCE@metadata$seurat$obj, "Seurat")) {

       if (varFeatures) {

-        methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@var.features <-

-          logical()

-        methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@meta.features <-

+        seurat.version <- .getSeuratObjectMajorVersion(inSCE@metadata$seurat$obj)

+        if (seurat.version >= 5.0) {

+          #methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@meta.data$var.features <-

+          #  logical()

+          methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@meta.data <-

           data.frame(row.names = make.unique(gsub("_", "-", rownames(inSCE))))

+        } 

+        else {

+          methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@var.features <-

+            logical()

+          methods::slot(inSCE@metadata$seurat$obj, "assays")[["RNA"]]@meta.features <-

+            data.frame(row.names = make.unique(gsub("_", "-", rownames(inSCE))))

+        }       

         inSCE@metadata$seurat$heatmap_pca <- NULL

       }

       if (PCA) {

Binary files a/docs/articles/ui_screenshots/ui_tutorial/qc_run.png and b/docs/articles/ui_screenshots/ui_tutorial/qc_run.png differ

@@ -119,7 +119,7 @@ if (is.null(reducedDimName)) {

 }

-### when 'sample' doesnn't exists in colData

+### when 'sample' doesn't exists in colData

 if (is.null(samples)) { samples <- "sample" }

 ```

@@ -1242,7 +1242,7 @@ if (skipSoupX_bg) {

   cat(paste0('## ', i, ' \n'))

   plotSoupX_bg <- tryCatch(

     {plotSoupXResults(inSCE = sce.qc, 

-                     soupXSample, 

+                     sceSample, 

                      combinePlot = "none",

                      background = TRUE)},

     error = function(e) {

@@ -1278,7 +1278,7 @@ for (sample in samples){

   cat("#### Soup Fractions {.tabset .tabset-fade} \n\n")

-  for (marker in names(plotSoupX$Sample[[sample]])[-1]) {

+  for (marker in names(plotSoupX_bg$Sample[[sample]])[-1]) {

     cat(paste0("##### ", marker, " {.tabset .tabset-fade} \n\n"))

     plot(plotSoupX_bg$Sample[[sample]][[marker]])

     cat("\n\n")

@@ -91,7 +91,7 @@ if(!showClusterDesc){

 }

 ```

-```{r, results='asis', warning=FALSE, message=FALSE, eval = !(plotTSNE && !is.null(metadata(data)$seurat$obj@reductions$tsne))}

+```{r, results='asis', warning=FALSE, message=FALSE, eval = !(plotTSNE && !is.null(metadata(data)$seurat$obj$reductions$tsne))}

 data <- runSeuratTSNE(data, useReduction = "pca", dims = significant_PC)

 ```

@@ -104,7 +104,6 @@ for(i in 1:(((maxResolution-minResolution)*10)+1)){

   cat(headingRES, " RES ", j, " {.tabset -} \n\n")

   cat(headingClust," Clusters {-} \n\n")

   p <- plotSeuratReduction(data, useReduction = "tsne", groupBy = paste0("Seurat_louvain_Resolution", j), showLegend = TRUE)

-  j <- j + 0.1

   print(p)

   cat("\n\n")

@@ -114,9 +113,10 @@ for(i in 1:(((maxResolution-minResolution)*10)+1)){

   cat("\n\n")

     cat(headingClust," Samples separated {-} \n\n")

-      p <- plotSeuratReduction(data, useReduction = "tsne", splitBy = biological.group, showLegend = TRUE)

+      p <- plotSeuratReduction(data, useReduction = "tsne", groupBy = paste0("Seurat_louvain_Resolution", j), splitBy = biological.group, showLegend = TRUE)

   print(p)

   cat("\n\n")

+  j <- j + 0.1

   if(!is.null(phenotype.groups)){

     cat(headingClust," Phenotype variable:", phenotype.groups," {-} \n\n")

@@ -127,7 +127,7 @@ for(i in 1:(((maxResolution-minResolution)*10)+1)){

 }

 ```

-```{r, results='asis', warning=FALSE, message=FALSE, eval = !(plotUMAP && !is.null(metadata(data)$seurat$obj@reductions$umap))}

+```{r, results='asis', warning=FALSE, message=FALSE, eval = !(plotUMAP && !is.null(metadata(data)$seurat$obj$reductions$umap))}

 data <- runSeuratUMAP(data, useReduction = "pca", dims = significant_PC)

 ```

@@ -140,7 +140,6 @@ for(i in 1:(((maxResolution-minResolution)*10)+1)){

   cat(headingRES, " RES ", j, " {.tabset -} \n\n")

   cat(headingClust," Clusters {-} \n\n")

   p <- plotSeuratReduction(data, useReduction = "umap", groupBy = paste0("Seurat_louvain_Resolution", j), showLegend = TRUE)

-  j <- j + 0.1

   print(p)

@@ -151,9 +150,10 @@ for(i in 1:(((maxResolution-minResolution)*10)+1)){

   cat("\n\n")

     cat(headingClust," Samples separated {-} \n\n")

-  p <- plotSeuratReduction(data, useReduction = "umap", splitBy = biological.group, showLegend = TRUE)

+  p <- plotSeuratReduction(data, useReduction = "umap", groupBy = paste0("Seurat_louvain_Resolution", j), splitBy = biological.group, showLegend = TRUE)

   print(p)

   cat("\n\n")

+  j <- j + 0.1

     if(!is.null(phenotype.groups)){

       cat(headingClust," Phenotype variable:", phenotype.groups," {-} \n\n")

@@ -58,7 +58,7 @@ cat(headingDR, " PCA {.tabset .tabset-fade}\n\n")

 To reduce the adverse effects of the inherent technical noise in single-cell data on downstream clustering, reduced dimensions are computed where each dimension represents a set of correlated features. However, an important task is to select the number of components that should be utilized by the downstream methods. To select the number of principal components that should be used in the downstream analysis, JackStraw and Elbow plot provide convenience in the selection of the significant components that contain most of the variability.  

-```{r, results='asis', warning=FALSE, eval = !(runDimRed && !is.null(metadata(data)$seurat$obj@reductions$pca)) || forceRun}

+```{r, results='asis', warning=FALSE, eval = !(runDimRed && !is.null(metadata(data)$seurat$obj$reductions$pca)) || forceRun}

 pcaParams <- list(

   inSCE = data,

   nPCs = pc.count,

@@ -94,8 +94,8 @@ ElbowPlot

 ```

 ```{r, echo=FALSE, warning=FALSE, eval= plotJackStraw}

-if(!is.null(metadata(data)$seurat$obj@reductions$pca@jackstraw)){

-  PC_Matrix <- metadata(data)$seurat$obj@reductions$pca@[email protected]

+if(!is.null(metadata(data)$seurat$obj$reductions$pca@jackstraw)){

+  PC_Matrix <- metadata(data)$seurat$obj$reductions$pca@jackstraw$overall.p.values

   significant_PC <- which.min(PC_Matrix[,2] < 0.01) - 1

 if (!exists("significant_PC") || significant_PC == 0){

@@ -129,7 +129,7 @@ JackStrawPlot

 PC.separated.height <- 3.5 * ceiling(pc.count/3)

 ```

-```{r, echo=FALSE, include=TRUE, eval = !(runDimRed && !is.null(metadata(data)$seurat$obj@reductions$pca))}

+```{r, echo=FALSE, include=TRUE, eval = !(runDimRed && !is.null(metadata(data)$seurat$obj$reductions$pca))}

 pcaParams$inSCE <- NULL

 pcaParams$significant_PC <- significant_PC

 metadata(data)$seurat$sctk$report$pcaParams <- pcaParams

@@ -54,7 +54,7 @@ cat(headingFS, " Feature Selection {}\n\n")

 Generally, a subset of features may represent the biological variation in the overall data and to better capture this true biological signal, it is recommended to identify this subset of features that often exhibit high cell-to-cell variation and use it in the downstream analysis instead of the full set of features. For this purpose, Seurat models the mean-to-variance relationship of the expression data by first computing *log of mean* and *log of variance* using *loess* and then standardizes the values using observed mean and expected variance. The overall variance of each feature is computed from the standardized values by clipping to a maximum value and ordering the features in the order of their variance. Lastly, top genes (by default *2000*) are selected as the top most variable features that represent the highest biological variability and used in the downstream methods.

-```{r, results='asis', warning=FALSE, message=FALSE, eval = !((runHVG && length(metadata(data)$seurat$obj@[email protected]) > 0)) || forceRun}

+```{r, results='asis', warning=FALSE, message=FALSE, eval = !((runHVG && length(metadata(data)$seurat$obj$RNA$var.features) > 0)) || forceRun}

 hvgParams <- list(

   inSCE = data,

   method = "vst", 

@@ -76,7 +76,7 @@ Labeled_Variable_data <- plotSeuratHVG(inSCE = data, labelPoints = 10)

 Labeled_Variable_data

 ```

-```{r, echo=FALSE, warning=FALSE, message=FALSE, include=FALSE, eval=!(runHVG && length(metadata(data)$seurat$obj@[email protected]) > 0)}

+```{r, echo=FALSE, warning=FALSE, message=FALSE, include=FALSE, eval=!(runHVG && length(metadata(data)$seurat$obj$RNA$var.features) > 0)}

 hvgParams$inSCE <- NULL

 hvgParams$labelPoints <- 10

 hvgParams$totalFeatures <- variable.features

@@ -7776,7 +7776,7 @@ shinyServer(function(input, output, session) {

     {

       req(vals$counts)

       message(paste0(date(), " ... Finding High Variable Genes"))

-      if(input$hvg_method == "vst" || packageVersion(pkg = "SeuratObject") >= 5.0){

+      if(input$hvg_method == "vst" || packageVersion(pkg = "SeuratObject") >= "5.0"){

         vals$counts <- runSeuratFindHVG(inSCE = vals$counts,

                                         useAssay = metadata(vals$counts)$sctk$seuratUseAssay,

                                         method = input$hvg_method,

@@ -7813,12 +7813,13 @@ shinyServer(function(input, output, session) {

   output$hvg_output <- renderText({

     req(vals$counts)

     if (!is.null(vals$counts@metadata$seurat$obj)) {

-      if(packageVersion(pkg = "SeuratObject") >= 5.0){

-        if (length(vals$counts@metadata$seurat$obj$RNA$"var.features") > 0) {

+      if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+        #if (length(vals$counts@metadata$seurat$obj$RNA$"var.features") > 0) {

           isolate({

+            

             singleCellTK:::.seuratGetVariableFeatures(vals$counts, input$hvg_no_features_view)

           })

-        }

+        #}

       }

       else{

         if (length(slot(vals$counts@metadata$seurat$obj, "assays")[["RNA"]]@var.features) > 0) {

@@ -8113,8 +8114,8 @@ shinyServer(function(input, output, session) {

     msg = "Please wait while clusters are being computed. See console log for progress.",

     {

       req(vals$counts)

-      if(packageVersion(pkg = "SeuratObject") >= 5.0){

-        pathToCluster = vals$counts@metadata$seurat$obj$"reductions"[[input$reduction_clustering_method]]

+      if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+        pathToCluster = vals$counts@metadata$seurat$obj@reductions[[input$reduction_clustering_method]]

       }

       else

         pathToCluster = vals$counts@metadata$seurat$obj@"reductions"[[input$reduction_clustering_method]]

@@ -8137,8 +8138,8 @@ shinyServer(function(input, output, session) {

         updateCollapse(session = session, "SeuratUI", style = list("Clustering" = "success"))

         message(paste0(date(), " ... Finding Clusters Complete"))

-        if(packageVersion(pkg = "SeuratObject") >= 5.0){

-          pathToUMAP = vals$counts@metadata$seurat$obj$"reductions"[["umap"]]

+        if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+          pathToUMAP = vals$counts@metadata$seurat$obj@reductions[["umap"]]

         }

         else

           pathToUMAP = vals$counts@metadata$seurat$obj@"reductions"[["umap"]]

@@ -8164,8 +8165,8 @@ shinyServer(function(input, output, session) {

             condition = !is.null(pathToUMAP))

         }

-        if(packageVersion(pkg = "SeuratObject") >= 5.0){

-          pathToTSNE = vals$counts@metadata$seurat$obj$"reductions"[["tsne"]]

+        if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+          pathToTSNE = vals$counts@metadata$seurat$obj@reductions[["tsne"]]

         }

         else

           pathToTSNE = vals$counts@metadata$seurat$obj@"reductions"[["tsne"]]

@@ -8192,8 +8193,8 @@ shinyServer(function(input, output, session) {

             condition = !is.null(pathToTSNE))

         }

-        if(packageVersion(pkg = "SeuratObject") >= 5.0){

-          pathToPCA = vals$counts@metadata$seurat$obj$"reductions"[["pca"]]

+        if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+          pathToPCA = vals$counts@metadata$seurat$obj@reductions[["pca"]]

         }

         else

           pathToPCA = vals$counts@metadata$seurat$obj@"reductions"[["pca"]]

@@ -8219,8 +8220,8 @@ shinyServer(function(input, output, session) {

             condition = !is.null(pathToPCA))

         }

-        if(packageVersion(pkg = "SeuratObject") >= 5.0){

-          pathToICA = vals$counts@metadata$seurat$obj$"reductions"[["ica"]]

+        if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+          pathToICA = vals$counts@metadata$seurat$obj@reductions[["ica"]]

         }

         else

           pathToICA = vals$counts@metadata$seurat$obj@"reductions"[["ica"]]

@@ -8255,7 +8256,12 @@ shinyServer(function(input, output, session) {

         shinyjs::enable(selector = "#SeuratUI > div[value='Marker Gene Plots']")

         #MARKER SETTINGS

-        geneChoices <- rowData(vals$counts)$Symbol_TENx

+

+        # this doesn't work for the PBMC Seurat data

+

+        #geneChoices <- rowData(vals$counts)$Symbol_TENx

+        geneChoices <- rownames(vals$counts)

+

         updateSelectizeInput(session, "selectGenesMarkerPlots",

                           choices = geneChoices)

@@ -8433,7 +8439,7 @@ shinyServer(function(input, output, session) {

             x = t,

             fixed = TRUE)

         )

-        if(seurat.version >= 5.0){

+        if(seurat.version >= "5.0"){

           Idents(seuratObject, cells = unlist(cells[[i]])) <- groups[i]

         }

@@ -8522,7 +8528,7 @@ shinyServer(function(input, output, session) {

             x = t,

             fixed = TRUE)

         )

-        if(seurat.version >= 5.0){

+        if(seurat.version >= "5.0"){

           cells[[i]] = unlist(cells[[i]])

         }

         Idents(seuratObject, cells = cells[[i]]) <- groups[i]

@@ -8579,7 +8585,7 @@ shinyServer(function(input, output, session) {

         groupVariable = input$seuratFindMarkerSelectPhenotype,

         ncol = 2,

         combine = TRUE,

-        useReduction = input$seuratFeatureUseReduction

+        #useReduction = input$seuratFeatureUseReduction

       )

     })

     output$findMarkerDotPlot <- renderPlot({

@@ -8636,8 +8642,8 @@ shinyServer(function(input, output, session) {

     {

       req(vals$counts)

-      if(packageVersion(pkg = "SeuratObject") >= 5.0){

-        pathToTSNE = vals$counts@metadata$seurat$obj$"reductions"[[input$reduction_tsne_method]]

+      if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+        pathToTSNE = vals$counts@metadata$seurat$obj@reductions[[input$reduction_tsne_method]]

       }

       else

         pathToTSNE = vals$counts@metadata$seurat$obj@"reductions"[[input$reduction_tsne_method]]

@@ -8693,8 +8699,9 @@ shinyServer(function(input, output, session) {

     msg = "Please wait while UMAP is being computed. See console log for progress.",

     {

       req(vals$counts)

-      if(packageVersion(pkg = "SeuratObject") >= 5.0){

-        pathToUMAP = vals$counts@metadata$seurat$obj$"reductions"[[input$reduction_umap_method]]

+      if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+        #pathToUMAP = vals$counts@metadata$seurat$obj$"reductions"[[input$reduction_umap_method]]

+        pathToUMAP = vals$counts@metadata$seurat$obj@reductions[[input$reduction_umap_method]]

       }

       else

         pathToUMAP = vals$counts@metadata$seurat$obj@"reductions"[[input$reduction_umap_method]]

@@ -8817,178 +8824,182 @@ shinyServer(function(input, output, session) {

   #Disable Seurat tabs & reset collapse panel tabs

-  observe({

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

-      #If data is uploaded in data tab, enable first tab i.e. Normalization tab in Seurat workflow

-      shinyjs::enable(

-        selector = "#SeuratUI > div[value='Normalize Data']")

-      shinyjs::enable(

-        selector = "#ScanpyUI > div[value='Normalize Data']")

-      

-      #Proceed only if sce object has metadata slot

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

-        if(packageVersion(pkg = "SeuratObject") >= 5.0){

-          #Proceed only if sce object has seurat object stored in metadata slot

-          if(!is.null(vals$counts@metadata$seurat$obj)){

-            #If variableFeatures have been removed from sce object, reset HVG tab and reset/lock next tab

-            if(length(vals$counts@metadata$seurat$obj$RNA$"var.features") <= 0){

-              updateCollapse(session = session, "SeuratUI", style = list("Highly Variable Genes" = "primary"))

-              updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

-              shinyjs::disable(selector = "#SeuratUI > div[value='Dimensionality Reduction']")

-            }

+  

+  # Try deleting this chunk of Seurat code and see if the image still runs

+  

+

+  # observe({

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

+  #     #If data is uploaded in data tab, enable first tab i.e. Normalization tab in Seurat workflow

+  #     shinyjs::enable(

+  #       selector = "#SeuratUI > div[value='Normalize Data']")

+  #     shinyjs::enable(

+  #       selector = "#ScanpyUI > div[value='Normalize Data']")

+      

+  #     #Proceed only if sce object has metadata slot

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

+  #       if(packageVersion(pkg = "SeuratObject") >= "5.0"){

+  #         #Proceed only if sce object has seurat object stored in metadata slot

+  #         if(!is.null(vals$counts@metadata$seurat$obj)){

+  #           #If variableFeatures have been removed from sce object, reset HVG tab and reset/lock next tab

+  #           if(length(vals$counts@metadata$seurat$obj$RNA$"var.features") <= 0){

+  #             updateCollapse(session = session, "SeuratUI", style = list("Highly Variable Genes" = "primary"))

+  #             updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

+  #             shinyjs::disable(selector = "#SeuratUI > div[value='Dimensionality Reduction']")

+  #           }

-            #Proceed if reduction slot is present in seurat object in metadata slot

-            if("reductions" %in% names(vals$counts@metadata$seurat$obj)){

+  #           #Proceed if reduction slot is present in seurat object in metadata slot

+  #           if("reductions" %in% names(vals$counts@metadata$seurat$obj)){

-              #If PCA and ICA both removed from sce object, reset DR tab and reset/lock next tab

-              if(is.null(vals$counts@metadata$seurat$obj$reductions$pca)

-                 && is.null(vals$counts@metadata$seurat$obj$reductions$ica)){

-                updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

-                updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

-                shinyjs::disable(selector = "#SeuratUI > div[value='2D-Embedding']")

-              }

+  #             #If PCA and ICA both removed from sce object, reset DR tab and reset/lock next tab

+  #             if(is.null(vals$counts@metadata$seurat$obj@reductions$pca)

+  #                && is.null(vals$counts@metadata$seurat$obj@reductions$ica)){

+  #               updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

+  #               updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

+  #               shinyjs::disable(selector = "#SeuratUI > div[value='2D-Embedding']")

+  #             }

-              #If TSNE and UMAP both removed from sce object, reset 2D-Embedding tab and reset/lock next tab

-              if(is.null(vals$counts@metadata$seurat$obj$reductions$tsne)

-                 && is.null(vals$counts@metadata$seurat$obj$reductions$umap)){

-                updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

-                updateCollapse(session = session, "SeuratUI", style = list("Clustering" = "primary"))

-                shinyjs::disable(selector = "#SeuratUI > div[value='Clustering']")

-              }

+  #             #If TSNE and UMAP both removed from sce object, reset 2D-Embedding tab and reset/lock next tab

+  #             if(is.null(vals$counts@metadata$seurat$obj@reductions$tsne)

+  #                && is.null(vals$counts@metadata$seurat$obj@reductions$umap)){

+  #               updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

+  #               updateCollapse(session = session, "SeuratUI", style = list("Clustering" = "primary"))

+  #               shinyjs::disable(selector = "#SeuratUI > div[value='Clustering']")

+  #             }

-              #If seurat cluster information removed from sce object, reset Clustering tab

-              if(!"seurat_clusters" %in% names(vals$counts@metadata$seurat$obj$meta.data)){

-                updateCollapse(session = session, "SeuratUI", style = list("Clustering" = "primary"))

-                updateCollapse(session = session, "SeuratUI", style = list("Find Markers" = "primary"))

-                shinyjs::disable(selector = "#SeuratUI > div[value='Find Markers']")

-              }

-            }

+  #             #If seurat cluster information removed from sce object, reset Clustering tab

+  #             if(!"seurat_clusters" %in% names(vals$counts@[email protected])){

+  #               updateCollapse(session = session, "SeuratUI", style = list("Clustering" = "primary"))

+  #               updateCollapse(session = session, "SeuratUI", style = list("Find Markers" = "primary"))

+  #               shinyjs::disable(selector = "#SeuratUI > div[value='Find Markers']")

+  #             }

+  #           }

-          }

+  #         }

-        }

-        else{

-          #Proceed only if sce object has seurat object stored in metadata slot

-          if(!is.null(vals$counts@metadata$seurat$obj)){

-            # #If seuratScaledData has been removed from sce object, reset Scale Data tab and reset/lock its next tab

-            # if(!"seuratScaledData" %in% expDataNames(vals$counts)){

-            #   updateCollapse(session = session, "SeuratUI", style = list("Scale Data" = "primary"))

-            #   updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

-            #   shinyjs::disable(selector = "div[value='Dimensionality Reduction']")

-            # }

+  #       }

+  #       else{

+  #         #Proceed only if sce object has seurat object stored in metadata slot

+  #         if(!is.null(vals$counts@metadata$seurat$obj)){

+  #           # #If seuratScaledData has been removed from sce object, reset Scale Data tab and reset/lock its next tab

+  #           # if(!"seuratScaledData" %in% expDataNames(vals$counts)){

+  #           #   updateCollapse(session = session, "SeuratUI", style = list("Scale Data" = "primary"))

+  #           #   updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

+  #           #   shinyjs::disable(selector = "div[value='Dimensionality Reduction']")

+  #           # }

-            #If variableFeatures have been removed from sce object, reset HVG tab and reset/lock next tab

-            if(length(slot(vals$counts@metadata$seurat$obj, "assays")[["RNA"]]@var.features) <= 0){

-              updateCollapse(session = session, "SeuratUI", style = list("Highly Variable Genes" = "primary"))

-              updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

-              shinyjs::disable(selector = "#SeuratUI > div[value='Dimensionality Reduction']")

-            }

+  #           #If variableFeatures have been removed from sce object, reset HVG tab and reset/lock next tab

+  #           if(length(slot(vals$counts@metadata$seurat$obj, "assays")[["RNA"]]@var.features) <= 0){

+  #             updateCollapse(session = session, "SeuratUI", style = list("Highly Variable Genes" = "primary"))

+  #             updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

+  #             shinyjs::disable(selector = "#SeuratUI > div[value='Dimensionality Reduction']")

+  #           }

-            #Proceed if reduction slot is present in seurat object in metadata slot

-            if("reductions" %in% slotNames(vals$counts@metadata$seurat$obj)){

+  #           #Proceed if reduction slot is present in seurat object in metadata slot

+  #           if("reductions" %in% slotNames(vals$counts@metadata$seurat$obj)){

-              #If PCA and ICA both removed from sce object, reset DR tab and reset/lock next tab

-              if(is.null(slot(vals$counts@metadata$seurat$obj, "reductions")[["pca"]])

-                 && is.null(slot(vals$counts@metadata$seurat$obj, "reductions")[["ica"]])){

-                updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

-                updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

-                shinyjs::disable(selector = "#SeuratUI > div[value='2D-Embedding']")

-              }

+  #             #If PCA and ICA both removed from sce object, reset DR tab and reset/lock next tab

+  #             if(is.null(slot(vals$counts@metadata$seurat$obj, "reductions")[["pca"]])

+  #                && is.null(slot(vals$counts@metadata$seurat$obj, "reductions")[["ica"]])){

+  #               updateCollapse(session = session, "SeuratUI", style = list("Dimensionality Reduction" = "primary"))

+  #               updateCollapse(session = session, "SeuratUI", style = list("2D-Embedding" = "primary"))

+  #               shinyjs::disable(selector = "#SeuratUI > div[value='2D-Embedding']")