diff --git a/DESCRIPTION b/DESCRIPTION
index 4d9c7e17..0b203383 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: SCHNAPPs
 Type: Package
 Title: Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data
-Version: 1.15.17
+Version: 1.15.18
 Authors@R: c(person("Bernd", "Jagla", role = c("aut", "cre"), email = "bernd.jagla@pasteur.fr", comment = c(ORCID = "0000-0002-7696-0484")))
 Maintainer: Bernd Jagla <bernd.jagla@pasteur.fr>
 Description: Single Cell sHiny APPlication (SCHNAPPs) is a R/Shiny based application to interact, manipulate, explore, and analyze single cell RNA-seq experiments, including MARS-seq and others.
diff --git a/README.md b/README.md
index 4c004988..49459ba0 100755
--- a/README.md
+++ b/README.md
@@ -22,10 +22,11 @@ Windows: <https://cran.r-project.org/bin/windows/>
 
 MAC: <https://cran.r-project.org/bin/macosx/>
 
-    update.packages()
+   
     if (!require("devtools"))
       install.packages("devtools")
     # devtools::install_github("mul118/shinyMCE")
+     update.packages()
     if (!requireNamespace("BiocManager", quietly = TRUE))
         install.packages("BiocManager")
     # update bioconductor packages if required
diff --git a/inst/app/contributions/DE_DataExploration/parameters.R b/inst/app/contributions/DE_DataExploration/parameters.R
index fedad491..ba9a230d 100644
--- a/inst/app/contributions/DE_DataExploration/parameters.R
+++ b/inst/app/contributions/DE_DataExploration/parameters.R
@@ -19,15 +19,15 @@ myNormalizationChoices <- list(
 myNormalizationParameters <- list(
   DE_logNormalization = tagList(
     sc_numericInput("DE_logNormalization_sf",
-                 label = "scale by (0 => minvalue)",
-                 min = 0, max = 200000, step = 1, value = defaultValue("DE_logNormalization_sf", 0)
+                    label = "scale by (0 => minvalue)",
+                    min = 0, max = 200000, step = 1, value = defaultValue("DE_logNormalization_sf", 0)
     )
-    ),
+  ),
   DE_scaterNormalization = h5("no Parameters implemented"),
   DE_seuratSCTnorm = tagList(
     sc_numericInput("DE_seuratSCTnorm_nHVG",
-                 label = "Number of variable genes",
-                 min = 10, max = 200000, step = 1, value = 3000
+                    label = "Number of variable genes",
+                    min = 10, max = 200000, step = 1, value = 3000
     ),
     sc_selectInput(
       "DE_seuratSCTnorm_var2reg",
@@ -42,8 +42,8 @@ myNormalizationParameters <- list(
   ),
   DE_seuratLogNorm = tagList(
     sc_numericInput("DE_seuratLogNorm_nHVG",
-                 label = "Number of variable genes",
-                 min = 10, max = 200000, step = 1, value = 3000
+                    label = "Number of variable genes",
+                    min = 10, max = 200000, step = 1, value = 3000
     ),
     sc_selectInput(
       "DE_seuratLogNorm_var2reg",
@@ -59,23 +59,23 @@ myNormalizationParameters <- list(
   DE_logGeneNormalization = sc_textInput(inputId = "DE_geneIds_norm", label = "comma separated list of genes used for normalization", value = ""),
   DE_seuratStandard = tagList(
     sc_numericInput("DE_seuratStandard_dims",
-                 label = "Which dimensions to use from the CCA to specify the neighbor search space",
-                 min = 2, max = 20000, step = 1, value = 30
+                    label = "Which dimensions to use from the CCA to specify the neighbor search space",
+                    min = 2, max = 20000, step = 1, value = 30
     ),
     sc_numericInput("DE_seuratStandard_anchorF",
-                 label = "select the provided number of features to be used in anchor finding",
-                 min = 60, max = 30000, step = 10,
-                 value = 2000
+                    label = "select the provided number of features to be used in anchor finding",
+                    min = 60, max = 30000, step = 10,
+                    value = 2000
     ),
     sc_numericInput("DE_seuratStandard_kF",
-                 label = "How many neighbors (k) to use when filtering anchors",
-                 min = 2, max = 3000, step = 1,
-                 value = 200
+                    label = "How many neighbors (k) to use when filtering anchors",
+                    min = 2, max = 3000, step = 1,
+                    value = 200
     ),
     sc_numericInput("DE_seuratStandard_k.weight",
-                 label = "Number of neighbors to consider when weighting",
-                 min = 2, max = 3000, step = 1,
-                 value = 100
+                    label = "Number of neighbors to consider when weighting",
+                    min = 2, max = 3000, step = 1,
+                    value = 100
     ),
     sc_selectInput(
       "DE_seuratStandard_splitby",
@@ -89,8 +89,8 @@ myNormalizationParameters <- list(
   ),
   DE_seuratSCtransform = tagList(
     sc_numericInput("DE_seuratSCtransform_nhvg",
-                 label = "number of highly variable genes",
-                 min = 200, max = 400000, step = 10, value = 3000
+                    label = "number of highly variable genes",
+                    min = 200, max = 400000, step = 10, value = 3000
     ),
     sc_selectInput(
       "DE_seuratSCtransform_vars2regress",
@@ -103,31 +103,31 @@ myNormalizationParameters <- list(
       # options = list(maxItems = 20)
     ),
     sc_numericInput("DE_seuratSCtransform_dimsMin",
-                 label = "minimum dimension (PCA) to use",
-                 min = 1, max = 100, step = 1, value = 1
+                    label = "minimum dimension (PCA) to use",
+                    min = 1, max = 100, step = 1, value = 1
     ),
     sc_numericInput("DE_seuratSCtransform_dimsMax",
-                 label = "maximum dimension (PCA) to use",
-                 min = 3, max = 100, step = 1, value = 30
+                    label = "maximum dimension (PCA) to use",
+                    min = 3, max = 100, step = 1, value = 30
     ),
     sc_numericInput("DE_seuratSCtransform_nfeatures",
-                 label = "number of genes to keep for the integration step",
-                 min = 200, max = 400000, step = 10, value = 3000
+                    label = "number of genes to keep for the integration step",
+                    min = 200, max = 400000, step = 10, value = 3000
     ),
     sc_numericInput("DE_seuratSCtransform_k.anchor",
-                 label = "Number of anchors to use",
-                 min = 1, max = 100, step = 1,
-                 value = 5
+                    label = "Number of anchors to use",
+                    min = 1, max = 100, step = 1,
+                    value = 5
     ),
     sc_numericInput("DE_seuratSCtransform_k.filter",
-                 label = "How many neighbors (k) to use when filtering anchors, should be smaller than the lowest number of cells per sample",
-                 min = 1, max = 1000, step = 10,
-                 value = 200
+                    label = "How many neighbors (k) to use when filtering anchors, should be smaller than the lowest number of cells per sample",
+                    min = 1, max = 1000, step = 10,
+                    value = 200
     ),
     sc_numericInput("DE_seuratSCtransform_k.score",
-                 label = "k score",
-                 min = 1, max = 1000, step = 1,
-                 value = 30
+                    label = "k score",
+                    min = 1, max = 1000, step = 1,
+                    value = 30
     ),
     # sc_numericInput("DE_seuratSCtransform_scalingFactor",
     #              label = "Scaling to use for transformed data",
@@ -148,13 +148,13 @@ myNormalizationParameters <- list(
   ),
   DE_seuratRefBased = tagList(
     sc_numericInput("DE_seuratRefBased_nfeatures",
-                 label = "Number of features to retain/use",
-                 min = 200, max = 20000, step = 10, value = 3000
+                    label = "Number of features to retain/use",
+                    min = 200, max = 20000, step = 10, value = 3000
     ),
     sc_numericInput("DE_seuratRefBased_k.filter",
-                 label = "How many neighbors (k) to use when filtering anchors, should be smaller than the lowest number of cells per sample",
-                 min = 60, max = 30000, step = 10,
-                 value = 200
+                    label = "How many neighbors (k) to use when filtering anchors, should be smaller than the lowest number of cells per sample",
+                    min = 60, max = 30000, step = 10,
+                    value = 200
     ),
     # sc_numericInput("DE_seuratRefBased_scaleFactor",
     #              label = "Scaling to use for transformed data",
@@ -198,9 +198,9 @@ DE_seuratRefBasedFunc <- function(scEx, scExMat, nfeatures = 3000, k.filter = 10
         # not sure that NA would be a good solution
         # so we are asking to remove the cells manually
         if (sum(limitCells) < ncol(scEx)) {
-          errStr = paste("please remove the following cells:\n", 
+          errStr = paste("\n\nplease remove the following cells:\n", 
                          paste(colnames(scEx)[!limitCells],
-                               collapse = ", "))
+                               collapse = ", "),"\n\n")
           cat (file = stderr(), errStr)
           if (!is.null(getDefaultReactiveDomain())) {
             showNotification(errStr, id = "DE_seuratError", duration = NULL, type = "error")  
@@ -215,6 +215,12 @@ DE_seuratRefBasedFunc <- function(scEx, scExMat, nfeatures = 3000, k.filter = 10
         counts = scExMat,
         meta.data = meta.data
       )
+      rownameMap = tibble("scExName" = rownames(scExMat), "seurName" = str_replace_all(rownames(scExMat),"_","-"))
+      if(!all(rownameMap$seurName == rownames(seurDat))){
+        cat(file = stderr(), paste("\n\n!!!Error during Seurat normalization:\nrownames not equal\n\n\n"))
+        return(NULL)
+      }
+      
       seur.list <- SplitObject(seurDat, split.by = splitby)
       # for (i in 1:length(seur.list)) {
       #   seur.list[[i]] <- SCTransform(seur.list[[i]], verbose = TRUE)
@@ -265,7 +271,8 @@ DE_seuratRefBasedFunc <- function(scEx, scExMat, nfeatures = 3000, k.filter = 10
           k.weight = min(100, min(unlist(lapply(seur.list, ncol))))
         )
         # return matrix object!!!
-        integrated[["integrated"]]$scale.data  %>% as.matrix()
+        LayerData(GetAssay(seurDat),"scale.data") %>% as.matrix()
+        # integrated[["integrated"]]$scale.data  %>% as.matrix()
       } else {
         seur.list[[1]][["SCT"]]$scale.data  %>% as.matrix()
       }
@@ -287,9 +294,11 @@ DE_seuratRefBasedFunc <- function(scEx, scExMat, nfeatures = 3000, k.filter = 10
       return(NULL)
     }
   )
-  if (is.null(A)) {
+  if (is.null(A) || nrow(A)<2 || ncol(A)<2) {
     return(NULL)
   }
+  rownames(A) = (rownameMap[match(rownames(A), rownameMap$seurName),"scExName"] %>% as.vector())[[1]]
+  
   scEx_bcnorm <- SingleCellExperiment(
     assay = list(logcounts = as(A, "TsparseMatrix")),
     colData = colData(scEx)[colnames(A), , drop = FALSE],
@@ -399,9 +408,9 @@ DE_seuratSCtransformFunc <- function(scEx,
         # not sure that NA would be a good solution
         # so we are asking to remove the cells manually
         if (sum(limitCells) < ncol(scEx)) {
-          errStr = paste("please remove the following cells:\n", 
+          errStr = paste("\n\nplease remove the following cells:\n", 
                          paste(colnames(scEx)[!limitCells],
-                               collapse = ", "))
+                               collapse = ", "),"\n\n")
           cat (file = stderr(), errStr)
           if (!is.null(getDefaultReactiveDomain())) {
             showNotification(errStr, id = "DE_seuratError", duration = NULL, type = "error")  
@@ -411,13 +420,18 @@ DE_seuratSCtransformFunc <- function(scEx,
         # scEx = scEx[, limitCells]
         # meta.data = meta.data[limitCells,, drop = FALSE]
       }
-      if(vars2regress %in% names(colData(scEx))){
-        meta.data[,vars2regress] = colData(scEx)[,vars2regress]
+      if(all(vars2regress %in% names(colData(scEx)))){
+        meta.data = cbind(meta.data ,colData(scEx)[,c(vars2regress)])
       }
       seurDat <- CreateSeuratObject(
         counts = scExMat,
         meta.data = meta.data
       )
+      rownameMap = tibble("scExName" = rownames(scExMat), "seurName" = str_replace_all(rownames(scExMat),"_","-"))
+      if(!all(rownameMap$seurName == rownames(seurDat))){
+        cat(file = stderr(), paste("\n\n!!!Error during Seurat normalization:\nrownames not equal\n\n\n"))
+        return(NULL)
+      }
       
       seur.list <- SplitObject(seurDat, split.by = splitby)
       seur.list <- lapply(seur.list, FUN = function(x) SCTransform(object = x, 
@@ -461,7 +475,8 @@ DE_seuratSCtransformFunc <- function(scEx,
           verbose = DEBUG,
           k.weight = min(100, min(unlist(lapply(seur.list, ncol))))
         )
-        integrated@assays$integrated@scale.data
+        LayerData(GetAssay(seurDat),"scale.data") %>% as.matrix()
+        # integrated@assays$integrated@scale.data
       } else {
         seur.list[[1]]@assays$SCT@scale.data 
       }
@@ -483,10 +498,12 @@ DE_seuratSCtransformFunc <- function(scEx,
   
   # FeaturePlot(integrated, c("CCR7", "S100A4", "GZMB", "GZMK", "GZMH"))
   
-  if (is.null(A)) {
+  if (is.null(A) || nrow(A)<2 || ncol(A)<2) {
     return(NULL)
   }
   A=as.matrix(A)
+  rownames(A) = (rownameMap[match(rownames(A), rownameMap$seurName),"scExName"] %>% as.vector())[[1]]
+  
   scEx_bcnorm <- SingleCellExperiment(
     assay = list(logcounts = as(A, "TsparseMatrix")),
     colData = colData(scEx)[colnames(A), , drop = FALSE],
@@ -600,9 +617,9 @@ DE_seuratStandardfunc <- function(scEx, scExMat, dims = 10, anchorsF = 2000, kF
         # not sure that NA would be a good solution
         # so we are asking to remove the cells manually
         if (sum(limitCells) < ncol(scEx)) {
-          errStr = paste("please remove the following cells:\n", 
+          errStr = paste("\n\nplease remove the following cells:\n", 
                          paste(colnames(scEx)[!limitCells],
-                               collapse = ", "))
+                               collapse = ", "),"\n\n")
           cat (file = stderr(), errStr)
           if (!is.null(getDefaultReactiveDomain())) {
             showNotification(errStr, id = "DE_seuratError", duration = NULL, type = "error")  
@@ -619,14 +636,20 @@ DE_seuratStandardfunc <- function(scEx, scExMat, dims = 10, anchorsF = 2000, kF
         counts = assay(scEx, "counts"),
         meta.data = meta.data
       )
+      rownameMap = tibble("scExName" = rownames(scExMat), "seurName" = str_replace_all(rownames(scExMat),"_","-"))
+      if(!all(rownameMap$seurName == rownames(seurDat))){
+        cat(file = stderr(), paste("\n\n!!!Error during Seurat normalization:\nrownames not equal\n\n\n"))
+        return(NULL)
+      }
+      
       seur.list <- Seurat::SplitObject(seurDat, split.by = splitby)
       seur.list <- lapply(seur.list, FUN = function(x) {
         # parallel
         # plan("multiprocess", workers = 4)
         x <- Seurat::NormalizeData(x, verbose = DEBUG)
         x <- Seurat::FindVariableFeatures(x,
-                                  selection.method = "vst",
-                                  nfeatures = 2000, verbose = DEBUG
+                                          selection.method = "vst",
+                                          nfeatures = 2000, verbose = DEBUG
         )
       }
       )
@@ -653,6 +676,7 @@ DE_seuratStandardfunc <- function(scEx, scExMat, dims = 10, anchorsF = 2000, kF
         
         integrated <- Seurat::ScaleData(integrated, verbose = DEBUG)
         integrated[["integrated"]]["scale.data"]
+        
       } else {
         seur.list[[1]][["RNA"]]$counts
       }
@@ -664,10 +688,12 @@ DE_seuratStandardfunc <- function(scEx, scExMat, dims = 10, anchorsF = 2000, kF
       return(NULL)
     }
   )
-  if (is.null(A)) {
+  if (is.null(A) || nrow(A)<2 || ncol(A)<2) {
     return(NULL)
   }
-  A <- as.matrix(A)
+  # A <- as.matrix(A)
+  # A <- seurDat[["SCT"]]@scale.data %>% as.matrix()
+  A <- LayerData(GetAssay(seurDat),"scale.data") %>% as.matrix()
   scEx_bcnorm <- SingleCellExperiment(
     assay = list(logcounts = as(A, "TsparseMatrix")),
     colData = colData(scEx)[colnames(A), , drop = FALSE],
@@ -767,7 +793,7 @@ DE_seuratSCTnorm <- reactive({
   runThis <- DE_seuratSCTnormButton()
   nHVG =  isolate(input$DE_seuratSCTnorm_nHVG)
   var2reg =  isolate(input$DE_seuratSCTnorm_var2reg)
-
+  
   # if (length(var2reg)<1)
   if (is.null(scEx) | runThis == "") {
     if (DEBUG) {
@@ -815,19 +841,19 @@ DE_seuratSCTnormfunc <- function(scEx, scExMat, nHVG, var2reg) {
   if (is.null(var2reg)) {
     var2reg = NULL
     meta.data <- as.data.frame(cellMeta[, "sampleNames", drop = FALSE])
-  } else if(var2reg == "" ) {
+  } else if(length(var2reg) == 1 && var2reg == "" ) {
     var2reg = NULL
     meta.data <- as.data.frame(cellMeta[, "sampleNames", drop = FALSE])
   } else {
-    meta.data <- as.data.frame(cellMeta[, var2reg, drop = FALSE])
+    meta.data <- as.data.frame(cellMeta[, c(var2reg), drop = FALSE])
     limitCells = meta.data[,1] %in% levels(meta.data[,1])[table(meta.data[,1]) > 30]
     # we cannot remove cell here because this would change scEX and projections
     # not sure that NA would be a good solution
     # so we are asking to remove the cells manually
     if (sum(limitCells) < ncol(scEx)) {
-      errStr = paste("please remove the following cells:\n", 
+      errStr = paste("\n\nplease remove the following cells:\n", 
                      paste(colnames(scEx)[!limitCells],
-                           collapse = ", "))
+                           collapse = ", "),"\n\n")
       cat (file = stderr(), errStr)
       if (!is.null(getDefaultReactiveDomain())) {
         showNotification(errStr, id = "DE_seuratError", duration = NULL, type = "error")  
@@ -850,6 +876,11 @@ DE_seuratSCTnormfunc <- function(scEx, scExMat, nHVG, var2reg) {
       return(NULL)
     }
   )
+  rownameMap = tibble("scExName" = rownames(scExMat), "seurName" = str_replace_all(rownames(scExMat),"_","-"))
+  if(!all(rownameMap$seurName == rownames(seurDat))){
+    cat(file = stderr(), paste("\n\n!!!Error during Seurat normalization:\nrownames not equal\n\n\n"))
+    return(NULL)
+  }
   # UMI-based normalisation & logTransformation
   # browser()
   # parallel
@@ -863,7 +894,11 @@ DE_seuratSCTnormfunc <- function(scEx, scExMat, nHVG, var2reg) {
                          verbose = DEBUG) 
   
   
-  A <- seurDat[["SCT"]]@scale.data %>% as.matrix()
+  A <- GetAssay(seurDat)@scale.data %>% as.matrix()
+  if(is.null(A)  || nrow(A)<2 || ncol(A)<2){
+    return(NULL)
+  }
+  rownames(A) = (rownameMap[match(rownames(A), rownameMap$seurName),"scExName"] %>% as.vector())[[1]]
   scEx_bcnorm <- SingleCellExperiment(
     assay = list(logcounts = as(A, "TsparseMatrix")),
     colData = colData(scEx)[colnames(A), , drop = FALSE],
@@ -960,19 +995,19 @@ DE_seuratLogNormfunc <- function(scEx, scExMat, nHVG, var2reg) {
     var2reg = NULL
     meta.data <- as.data.frame(cellMeta[, "sampleNames", drop = FALSE])
     
-  } else if(var2reg == "" ) {
+  } else if((length(var2reg) == 1 && var2reg == "" )) {
     var2reg = NULL
     meta.data <- as.data.frame(cellMeta[, "sampleNames", drop = FALSE])
   } else {
-    meta.data <- as.data.frame(cellMeta[, var2reg, drop = FALSE])
+    meta.data <- as.data.frame(cellMeta[, c(var2reg), drop = FALSE])
     limitCells = meta.data[,1] %in% levels(meta.data[,1])[table(meta.data[,1]) > 30]
     # we cannot remove cell here because this would change scEX and projections
     # not sure that NA would be a good solution
     # so we are asking to remove the cells manually
     if (sum(limitCells) < ncol(scEx)) {
-      errStr = paste("please remove the following cells:\n", 
+      errStr = paste("\n\nplease remove the following cells:\n", 
                      paste(colnames(scEx)[!limitCells],
-                           collapse = ", "))
+                           collapse = ", "),"\n\n")
       cat (file = stderr(), errStr)
       if (!is.null(getDefaultReactiveDomain())) {
         showNotification(errStr, id = "DE_seuratError", duration = NULL, type = "error")  
@@ -983,7 +1018,7 @@ DE_seuratLogNormfunc <- function(scEx, scExMat, nHVG, var2reg) {
     # scEx = scEx[, limitCells]
     # meta.data = meta.data[limitCells,, drop = FALSE]
   }
- 
+  
   seurDat <- tryCatch(
     {
       seurDat <- CreateSeuratObject(
@@ -996,6 +1031,12 @@ DE_seuratLogNormfunc <- function(scEx, scExMat, nHVG, var2reg) {
       return(NULL)
     }
   )
+  rownameMap = tibble("scExName" = rownames(scExMat), "seurName" = str_replace_all(rownames(scExMat),"_","-"))
+  if(!all(rownameMap$seurName == rownames(seurDat))){
+    cat(file = stderr(), paste("\n\n!!!Error during Seurat normalization:\nrownames not equal\n\n\n"))
+    return(NULL)
+  }
+  
   # UMI-based normalisation & logTransformation
   # browser()
   # parallel
@@ -1012,7 +1053,12 @@ DE_seuratLogNormfunc <- function(scEx, scExMat, nHVG, var2reg) {
   seurDat = Seurat::ScaleData(object = seurDat,
                               vars.to.regress = var2reg)
   
-  A <- seurDat[["RNA"]]["scale.data"] %>% as.matrix()
+  A <- LayerData(GetAssay(seurDat),"scale.data") %>% as.matrix()
+  if(is.null(A) || nrow(A)<2 || ncol(A)<2){
+    return(NULL)
+  }
+  rownames(A) = (rownameMap[match(rownames(A), rownameMap$seurName),"scExName"] %>% as.vector())[[1]]
+  
   scEx_bcnorm <- SingleCellExperiment(
     assay = list(logcounts = as(A, "TsparseMatrix")),
     colData = colData(scEx)[colnames(A), , drop = FALSE],
@@ -1255,9 +1301,9 @@ DE_logNormalization <- reactive(label = "rlogNorm", {
   }
   # cp = load(file="~/SCHNAPPsDebug/DE_logNormalization.RData")
   if (is.null(sfactor)) {
-      sfactor = defaultValue("DE_logNormalization_sf", 0)
+    sfactor = defaultValue("DE_logNormalization_sf", 0)
   }
- 
+  
   # TODO ?? define scaling factor somewhere else???
   # sfactor <- max(max(assays(scEx)[["counts"]]), 1000)
   retVal <- DE_logNormalizationfunc(scEx, sfactor)
diff --git a/inst/app/contributions/coE_coExpression/reactives.R b/inst/app/contributions/coE_coExpression/reactives.R
index e0f27653..cf2abb3a 100644
--- a/inst/app/contributions/coE_coExpression/reactives.R
+++ b/inst/app/contributions/coE_coExpression/reactives.R
@@ -436,7 +436,7 @@ scranFindMarkerFullReactiveTable <- reactive({
   oldNcpu = bpnworkers(bpparam())
   on.exit({
     printTimeEnd(start.time, "coE_scranFindMarkerTableReact")
-    register(MulticoreParam(oldNcpu))
+    register(safeBPParam(oldNcpu))
     if (!is.null(getDefaultReactiveDomain())) {
       removeNotification(id = "coE_scranFindMarkerTableReact")
     }
@@ -467,7 +467,7 @@ scranFindMarkerFullReactiveTable <- reactive({
   # browser()
   # 4.18 GB
   # parallel --- done
-  register(MulticoreParam(nCPU))
+  register(safeBPParam(nCPU))
   
   start.time <- base::Sys.time()
   wmarkers <- tryCatch({
diff --git a/inst/app/contributions/sCA_subClusterAnalysis/reactives.R b/inst/app/contributions/sCA_subClusterAnalysis/reactives.R
index b8f4940c..7cabd0c3 100644
--- a/inst/app/contributions/sCA_subClusterAnalysis/reactives.R
+++ b/inst/app/contributions/sCA_subClusterAnalysis/reactives.R
@@ -683,7 +683,7 @@ sCA_dge <- reactive({
     register(SnowParam(workers = nCPU))
   } else{
     plan(multisession, workers = nCPU)
-    register(MulticoreParam(workers = nCPU))
+    register(safeBPParam(nCPU))
   }
   
   
diff --git a/inst/app/defaultValues.R b/inst/app/defaultValues.R
index c26e8202..35223c12 100644
--- a/inst/app/defaultValues.R
+++ b/inst/app/defaultValues.R
@@ -5,7 +5,7 @@
 allowedColors <- unique(c(
    "#2D96FA", "#8D8889", "#E8E0E0", "#FF2F7D", "#60A948", "#732BA3", "#FFC720", "#E96B0C", "#22ABA4", 
    "#8c510a", "#d8b365", "#f6e8c3", "#c7eae5", "#5ab4ac", "#01665e","#000000", "#c51b7d", "#e9a3c9", "#fde0ef", 
-   "#e0e0e0", "#FAF4F5", "#999999", "#414144", "#E3E9EB", "#D4070F", "#1C1AAF", "#4d4d4d", "#e6f5d0", "#a1d76a", "#4d9221", "#762a83","white", 
+   "#e0e0e0", "#FAF4F5", "#999999", "#414144", "#E3E9EB", "#D4070F", "#1C1AAF", "#4d4d4d", "#e6f5d0", "#a1d76a", "#4d9221", "#762a83", 
    "#af8dc3", "#e7d4e8", "#d9f0d3", "#7fbf7b", "#1b7837", "#b35806", "#f1a340", "#fee0b6", "#d8daeb", "#998ec3", 
    "#542788",  "#fddbc7", "#d1e5f0", "#ef8a62", "#b2182b", "#67a9cf", "#2166ac"))
 names(allowedColors) = make.names(1:length(allowedColors))
diff --git a/inst/app/outputs.R b/inst/app/outputs.R
index 24208990..61d6641a 100644
--- a/inst/app/outputs.R
+++ b/inst/app/outputs.R
@@ -180,18 +180,18 @@ observe(label ="obs_pcaN", x = {
 })
 
 
-# check gene names ----
-observe({
-  scEx = scEx()
-  req(scEx)
-  if(any(stringr::str_detect( rownames(scEx), "_"))){
-    showNotification(
-      "gene names contain '_', which will be replaced by Seurat by '.', which can cause artefacts",
-      type = "error",
-      duration = NULL
-    )
-  }
-})
+# # check gene names ----
+# observe({
+#   scEx = scEx()
+#   req(scEx)
+#   if(any(stringr::str_detect( rownames(scEx), "_"))){
+#     showNotification(
+#       "gene names contain '_', which will be replaced by Seurat by '.', which can cause artefacts",
+#       type = "error",
+#       duration = NULL
+#     )
+#   }
+# })
 
 
 output$noLogWarning <- renderText({
diff --git a/inst/app/reactives.R b/inst/app/reactives.R
index 72259fcb..6b9f4bd4 100644
--- a/inst/app/reactives.R
+++ b/inst/app/reactives.R
@@ -1842,10 +1842,18 @@ scEx_log <- reactive({
   } else {
     scEx_log <- do.call(normMethod, args = list())
   }
+  # browser()
   if (is.null(scEx_log)) {
     # problem with normalization
     return(NULL)
   }
+  if(nrow(scEx_log)<2){
+    cat(file = stderr(), "\n\nnormalization returned 0 genes.\n\n\n")
+    return(NULL)
+  }
+  if(ncol(scEx_log)<2){
+    return(NULL)
+  }
   .schnappsEnv$calculated_normalizationRadioButton <- normMethod
   
   add2history(type = "save", input = isolate( reactiveValuesToList(input)), comment = "scEx_log", scEx_log = scEx_log)
@@ -2148,6 +2156,34 @@ pcaFunc <- function(scEx, scEx_log,
     return(val)
   }
   
+  if(nrow(scEx_log)<10){
+    cat(file = stderr(), paste("error in PCA:", e))
+    if (!is.null(getDefaultReactiveDomain())) {
+      showNotification(
+        paste("Problem with PCA, probably not enough genes?", e),
+        type = "warning",
+        id = "pcawarning",
+        duration = NULL
+      )
+    }
+    cat(file = stderr(), "PCA FAILED!!!\n")
+    return(NULL)
+  }
+  
+  if(ncol(scEx_log)<10){
+    cat(file = stderr(), paste("error in PCA:", e))
+    if (!is.null(getDefaultReactiveDomain())) {
+      showNotification(
+        paste("Problem with PCA, probably not enough cells?", e),
+        type = "warning",
+        id = "pcawarning",
+        duration = NULL
+      )
+    }
+    cat(file = stderr(), "PCA FAILED!!!\n")
+    return(NULL)
+  }
+  
   scaterPCA <- withWarnings({
     # not sure, but this works on another with TsparseMatrix
     if (!is(assays(scEx_log)[["logcounts"]], "CsparseMatrix")) {
@@ -2182,6 +2218,9 @@ pcaFunc <- function(scEx, scEx_log,
     pca
   })
   
+  if(!exists("scaterPCA")){
+    return(NULL)
+  }
   if (is.null(scaterPCA)) {
     return(NULL)
   }
@@ -3213,7 +3252,7 @@ projections <- reactive({
   printTimeEnd(start.time, "projections add history")
   add2history(type = "save", input=isolate( reactiveValuesToList(input)), comment = "projections", projections = projections)
   
-  cat(file = stderr(), paste("\n\nscLog: ",isolate(input$whichscLog),"\n\n"))
+  if (DEBUG) cat(file = stderr(), paste("scLog: ",isolate(input$whichscLog),"\n"))
   # add2history(type = "save", comment = "projections", projections = projections)
   
   exportTestValues(projections = {
diff --git a/inst/app/runDevApp.R b/inst/app/runDevApp.R
index 9269eca8..f3914044 100644
--- a/inst/app/runDevApp.R
+++ b/inst/app/runDevApp.R
@@ -23,7 +23,7 @@ plan("multisession", workers = 8)
 # plan(callr, workers = 4)
 
 library("BiocParallel")
-register(MulticoreParam(2))
+register(safeBPParam(2))
 # register(SerialParam())
 
 localContributionDir = "~/Rstudio/SCHNAPPsContributions/working"
@@ -51,7 +51,7 @@ historyPath = "/Volumes/LaCie2022/RStudio_history/julia/"
 # historyPath = "/Volumes/CBUtechsZeus/bernd/celia/hist_2023-May-26.15.18/"
 # # historyPath = "demoHistory/MPI"
 # # historyPath = "/Volumes/LaCie2022/RStudio_history/marielle/hist_2022-Dec-15.18.15/"
-# historyPath = NULL
+historyPath = NULL
 assign(".SCHNAPPs_locContributionDir", localContributionDir, envir = .schnappsEnv)
 assign(".SCHNAPPs_defaultValueSingleGene", defaultValueSingleGene, envir = .schnappsEnv)
 assign(".SCHNAPPs_defaultValueMultiGenes", defaultValueMultiGenes, envir = .schnappsEnv)
diff --git a/inst/app/runVMApp.R b/inst/app/runVMApp.R
index f221dadd..85a2b8cd 100644
--- a/inst/app/runVMApp.R
+++ b/inst/app/runVMApp.R
@@ -20,7 +20,7 @@ library(doParallel)
 registerDoParallel(cores=WORKERS)
 
 library("BiocParallel")
-register(MulticoreParam(WORKERS))
+register(safeBPParam(WORKERS))
 # register(SerialParam())
 
 localContributionDir = "/home/schnapps/SCHNAPPsContributions/"
diff --git a/inst/app/serverFunctions.R b/inst/app/serverFunctions.R
index 9af29fd2..46c4bb7c 100644
--- a/inst/app/serverFunctions.R
+++ b/inst/app/serverFunctions.R
@@ -16,6 +16,15 @@ suppressMessages(library(InteractiveComplexHeatmap))
 library(dendsort)
 library(MASS)
 
+# from LTLA (https://github.com/Bioconductor/BiocParallel/issues/98)
+safeBPParam <- function(nworkers) {
+  if (.Platform$OS.type=="windows") {
+    BiocParallel::SerialParam()
+  } else {
+    BiocParallel::MulticoreParam(nworkers)
+  }
+}
+
 
 ### Try catch from extended examples ----
 #' tryCatch with Warning Extraction
@@ -1551,7 +1560,7 @@ heatmapModuleFunction <- function(
   if (is.null(sortingCols)) return(NULL)
   if (sortingCols == "dendrogram") colTree = TRUE
   
-  if (is.null(heatmapData) | is.null(proje) | is.null(heatmapData$mat)) {
+  if (is.null(heatmapData) | is.null(proje) | is.null(heatmapData$mat) ) {
     return(NULL)
     # return(list(
     #   src = "empty.png",
@@ -1561,6 +1570,9 @@ heatmapModuleFunction <- function(
     #   alt = "pHeatMapPlot should be here (null)"
     # ))
   }
+  if(nrow(heatmapData$mat)<2 | ncol(heatmapData$mat)<2){
+    return(NULL)
+  }
   if(is.null(minMaxVal)) minMaxVal = c(min(heatmapData$mat), max(heatmapData$mat))
   if (.schnappsEnv$DEBUGSAVE) {
     save(file = "~/SCHNAPPsDebug/heatmapModuleFunction.RData", list = c(ls()))
diff --git a/inst/develo/dockerCelia/runDockerApp.R b/inst/develo/dockerCelia/runDockerApp.R
index 0cddcaf8..85f83429 100644
--- a/inst/develo/dockerCelia/runDockerApp.R
+++ b/inst/develo/dockerCelia/runDockerApp.R
@@ -19,7 +19,7 @@ plan(sequential)
 
 
 library("BiocParallel")
-register(MulticoreParam(WORKERS))
+register(safeBPParam(WORKERS))
 # register(SerialParam())
 
 localContributionDir = "/root/SCHNAPPsContributions/"
diff --git a/inst/develo/dockerImage/runDockerApp.R b/inst/develo/dockerImage/runDockerApp.R
index 0cddcaf8..85f83429 100644
--- a/inst/develo/dockerImage/runDockerApp.R
+++ b/inst/develo/dockerImage/runDockerApp.R
@@ -19,7 +19,7 @@ plan(sequential)
 
 
 library("BiocParallel")
-register(MulticoreParam(WORKERS))
+register(safeBPParam(WORKERS))
 # register(SerialParam())
 
 localContributionDir = "/root/SCHNAPPsContributions/"
diff --git a/inst/develo/params-tests.R b/inst/develo/params-tests.R
index fabe8b3a..af8918e3 100644
--- a/inst/develo/params-tests.R
+++ b/inst/develo/params-tests.R
@@ -12,14 +12,14 @@ params <- list(
 params$assay.type <- "counts"
 params$x <- scEx
 
-register(MulticoreParam(
-  workers = ifelse(detectCores() > 1, detectCores() - 1, 1)
+register(safeBPParam(
+ ifelse(detectCores() > 1, detectCores() - 1, 1)
 ),
 default = TRUE
 )
 
-register(MulticoreParam(
-  workers = 13
+register(safeBPParam(
+  13
 ),
 default = TRUE
 )
diff --git a/inst/develo/startSchnapps.R b/inst/develo/startSchnapps.R
index 487ac9f6..1c7f7c8b 100755
--- a/inst/develo/startSchnapps.R
+++ b/inst/develo/startSchnapps.R
@@ -15,7 +15,7 @@ library(future)
 plan(sequential)
 
 library("BiocParallel")
-register(MulticoreParam(6))
+register(safeBPParam(6))
 
 schnapps(DEBUG=T)