diff --git a/.github/workflows/conda.yml b/.github/workflows/conda.yml
index 1d67cf3..4e7f93f 100644
--- a/.github/workflows/conda.yml
+++ b/.github/workflows/conda.yml
@@ -106,7 +106,7 @@ jobs:
           source "${HOME}/conda/etc/profile.d/conda.sh"
           conda activate ../env
 
-          Rscript -e "setRepositories(ind=1:5); remotes::install_github('NICHD-BSPC/carnation', upgrade='never')"
+          Rscript -e "setRepositories(ind=1:5); remotes::install_github('NICHD-BSPC/carnation@r4.3', upgrade='never')"
           Rscript -e "library(carnation)"
 
 
diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml
index b2e578c..b3f8af7 100644
--- a/.github/workflows/pkgdown.yaml
+++ b/.github/workflows/pkgdown.yaml
@@ -61,7 +61,7 @@ jobs:
           source "${HOME}/conda/etc/profile.d/conda.sh"
           conda activate ../env
 
-          Rscript -e "setRepositories(ind=1:5); remotes::install_github('NICHD-BSPC/carnation', upgrade='never')"
+          Rscript -e "setRepositories(ind=1:5); remotes::install_github('NICHD-BSPC/carnation@r4.3', upgrade='never')"
           Rscript -e "pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)"
 
       - name: Deploy to GitHub pages 🚀
diff --git a/DESCRIPTION b/DESCRIPTION
index fd45eb7..7198b0d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,23 +1,27 @@
 Package: carnation
-Title: Shiny App to Explore RNA-Seq Analysis
-Version: 0.99.8
+Title: Interactive Exploration & Management of RNA-Seq Analyses
+Version: 0.99.9
 Authors@R:
     c(
         person("Apratim", "Mitra", , "apratim.mitra@nih.gov",
                role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3279-0054")),
+        person(c("Matthew", "Tyler"), "Menold", , "matthew.menold@gmail.com",
+               role = c("ctb"), comment = c(ORCID = "0009-0007-4728-2470")),
         person("Ryan", "Dale", , "ryan.dale@nih.gov",
                role = c("fnd"), comment = c(ORCID = "0000-0003-2664-3744"))
     )
-Description: Interactive Shiny dashboard app that can be used to
-    explore RNA-Seq analysis results including differential expression (DE),
+Description: This package provides a highly interactive & modular shiny app to
+    explore three facets of RNA-Seq analysis: differential expression (DE),
     functional enrichment and pattern analysis. Several visualizations
     are implemented to provide a wide-ranging view of data sets. For
     DE analysis, we provide PCA plot, MA plot, Upset plot & heatmaps,
     in addition to a highly customizable gene plot.  Seven different
     visualizations are available for functional enrichment analysis,
-    and we also support gene pattern analysis. In addition, the app
-    provides a platform to manage multiple projects and user groups
-    that can be run on a central server.
+    and we also support gene pattern analysis. Genes of interest can
+    be tracked across all modules using the gene scratchpad. In addition,
+    carnation provides an integrated platform to manage multiple projects
+    and user access that can be run on a central server to share with
+    collaborators.
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
diff --git a/NAMESPACE b/NAMESPACE
index a638950..723b20e 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -43,6 +43,7 @@ export(horizonUI)
 export(in_admin_group)
 export(install_carnation)
 export(is_site_admin)
+export(is_valid_pattern_obj)
 export(loadDataServer)
 export(loadDataUI)
 export(maPlotServer)
@@ -155,13 +156,17 @@ importFrom(htmltools,tags)
 importFrom(htmltools,withTags)
 importFrom(igraph,"V<-")
 importFrom(igraph,V)
+importFrom(methods,.hasSlot)
 importFrom(methods,new)
 importFrom(plotly,add_markers)
 importFrom(plotly,add_trace)
+importFrom(plotly,event_data)
+importFrom(plotly,event_register)
 importFrom(plotly,ggplotly)
 importFrom(plotly,layout)
 importFrom(plotly,plot_ly)
 importFrom(plotly,plotlyOutput)
+importFrom(plotly,plotlyProxy)
 importFrom(plotly,renderPlotly)
 importFrom(plotly,save_image)
 importFrom(plotly,toWebGL)
diff --git a/NEWS.md b/NEWS.md
index b4551c4..0552627 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,18 @@
 # carnation
 
+## v0.99.9
+
+- carnation now supports `edgeR` and `limma` output in differential
+  expression analysis.
+- The scatter plot now allows gene selection directly from the plot
+  and viewed in the table. Genes selected in the table can be added
+  to the gene scratchpad and tracked across the app.
+- The main loading page now shows the currently loaded dataset.
+  This prevents accidentally reloading or replacing the current
+  data.
+- Pattern analysis can now be added to a carnation object via
+  the `Load data` module, either in TSV or Rds format.
+
 ## v0.99.8
 
 - Add packages to `Suggests::` to address build issues.
diff --git a/R/app.R b/R/app.R
index 0e4323d..c90a509 100644
--- a/R/app.R
+++ b/R/app.R
@@ -453,7 +453,12 @@ run_carnation <- function(credentials=NULL, passphrase=NULL, enable_admin=TRUE,
 
             withSpinner(
               uiOutput('load_ui')
-            ) # withSpinner
+            ),  # withSpinner
+
+            br(),
+            fluidRow(
+              column(3, uiOutput('current_obj'))
+            ) # fluidRow
           ), # tabPanel
 
           tabPanel('DE analysis',
@@ -647,6 +652,9 @@ run_carnation <- function(credentials=NULL, passphrase=NULL, enable_admin=TRUE,
     # list to hold original object and file path
     original <- reactiveValues(obj=NULL, path=NULL)
 
+    # reactiveValues to hold loaded project
+    current <- reactiveValues(proj=NULL, analysis=NULL)
+
     # list to hold user details
     user_details <- reactiveValues(username=NULL, admin=FALSE)
 
@@ -1073,6 +1081,46 @@ run_carnation <- function(credentials=NULL, passphrase=NULL, enable_admin=TRUE,
                                x
                            })
 
+      # make sure 'padj' & 'log2FoldChange' columns exist in res objects
+      # or supported alternatives exist
+      sanitized_res_list <- obj[[ res.name ]]
+
+      # supported column names
+      column_names <- config()$server$de_analysis$column_names
+      defaults <- names(column_names)
+
+      # these res objects will be dropped
+      drop_res_names <- NULL
+
+      for(name in names(sanitized_res_list)){
+        res <- sanitized_res_list[[ name ]]$res
+        res <- as.data.frame(res)
+
+        for(cname in defaults){
+          idx <- colnames(res) %in% column_names[[ cname ]]
+
+          # if matches exist
+          if(sum(idx) > 0){
+            if(sum(idx) > 1){
+            # only use the first match if multiple matches
+            # and show warning
+              message('Warning: Ambiguous ', cname, 'column for ', name, '.\nUsing ', colnames(res)[which(idx)[1]])
+            }
+
+            idx <- which(idx)[1]
+            colnames(res)[idx] <- cname
+          } else {
+            message('Unsupported res type for ', name, ':', cname, ' column not found, skipping')
+            drop_res_names <- c(drop_res_names, name)
+          }
+        }
+        sanitized_res_list[[ name ]]$res <- res
+      }
+
+      # remove unsupported res objects
+      sanitized_res_list <- sanitized_res_list[ !names(sanitized_res_list) %in% drop_res_names ]
+      obj[[ res.name ]] <- sanitized_res_list
+
       # add obj slots to reactive values
       obj <- make_final_object(obj)
 
@@ -1237,8 +1285,28 @@ run_carnation <- function(credentials=NULL, passphrase=NULL, enable_admin=TRUE,
                         selected='DE analysis')
       updateTabsetPanel(session, inputId='de_mode',
                         selected='Summary')
+
+      # update current project
+      current$proj <- input$dds
+
+      al <- assay.list$l[[ input$dds ]]
+      idx <- which(unname(al) == input$assay)
+      current$analysis <- names(assay.list$l[[ input$dds ]])[idx]
+
     }) # observeEvent load data
 
+    # show loaded dataset
+    output$current_obj <- renderUI({
+      req(current$proj)
+
+      tags$div(
+        class='div-stats-card',
+        tags$p('Currently loaded:'),
+        tags$p('  - Project: ', tags$i(current$proj)),
+        tags$p('  - Analysis: ', tags$i(current$analysis))
+      )
+    })
+
     # update comparison menus after load
     observeEvent(app_object$res, {
       validate(
@@ -1604,7 +1672,25 @@ run_carnation <- function(credentials=NULL, passphrase=NULL, enable_admin=TRUE,
            gene.to.plot=gene_scratchpad())
     })
 
-    scatterPlotServer('scatterplot', app_object, scatterplot_args, config)
+    scatter_data <- scatterPlotServer('scatterplot',
+                                      app_object,
+                                      scatterplot_args,
+                                      gene_scratchpad,
+                                      reactive({ input$reset.genes }),
+                                      config)
+
+    observeEvent(scatter_data(), {
+      g <- scatter_data()$genes
+
+      # only update scratchpad if different genes returned
+      if(length(setdiff(g, input$gene.to.plot)) != 0){
+        # update gene selector with clicked genes
+        updateSelectizeInput(session, 'gene.to.plot',
+                             choices=gene.id$gene,
+                             selected=g,
+                             server=TRUE)
+      }
+    })
 
     ##################### UpSet plot #########################
 
diff --git a/R/carnation-pkg.R b/R/carnation-pkg.R
index 24cf3b7..874d4e3 100644
--- a/R/carnation-pkg.R
+++ b/R/carnation-pkg.R
@@ -12,5 +12,7 @@
 #' - Manage local data in single-user mode or deploy on a server to share with
 #'   collaborators using in-built user management system.
 #'
+#' Main function to run the app: [run_carnation()]
+#'
 #' @keywords internal
 '_PACKAGE'
diff --git a/R/functions.R b/R/functions.R
index edc6d7f..81724b1 100644
--- a/R/functions.R
+++ b/R/functions.R
@@ -448,6 +448,69 @@ get_y_init <- function(df, y_delta, pseudocount){
     return( c(min.init, max.init) )
 }
 
+#' Validate Pattern Analysis Object Schema
+#'
+#' Validate the schema for a single `degpatterns` analysis element used by the
+#' pattern analysis module.
+#'
+#' @param pattern_obj A single pattern analysis element. Must be either a
+#' `data.frame` or a list containing a `normalized` `data.frame`.
+#' @param require_symbol Logical, if `TRUE` require a `symbol` column in the
+#' analysis table.
+#'
+#' @return Returns `TRUE` when validation succeeds, otherwise returns `FALSE`
+#' after emitting a message describing the issue.
+#'
+#' @examples
+#' data(degpatterns_dex, package = "carnation")
+#'
+#' is_valid_pattern_obj(degpatterns_dex)
+#'
+#' @export
+is_valid_pattern_obj <- function(pattern_obj, require_symbol = FALSE){
+  if(is.null(pattern_obj)){
+    message('"pattern_obj" cannot be NULL')
+    return(FALSE)
+  }
+
+  req_cols <- c("genes", "value")
+  if(require_symbol) req_cols <- c(req_cols, "symbol")
+
+  if(is.data.frame(pattern_obj)){
+    df <- pattern_obj
+  } else if(is.list(pattern_obj) &&
+            "normalized" %in% names(pattern_obj) &&
+            is.data.frame(pattern_obj$normalized)){
+    df <- pattern_obj$normalized
+  } else {
+    message(
+      '"pattern_obj" must be a data.frame or a list containing a data.frame in "$normalized"'
+    )
+    return(FALSE)
+  }
+
+  missing_cols <- setdiff(req_cols, colnames(df))
+  if(length(missing_cols) > 0){
+    message(
+      '"pattern_obj" is missing required column(s): ',
+      paste(missing_cols, collapse = ", ")
+    )
+    return(FALSE)
+  }
+
+  # Pattern module expects at least one clustering column.
+  cluster_cols <- c("cluster", grep("^cutoff", colnames(df), value = TRUE))
+  if(!any(cluster_cols %in% colnames(df))){
+    message(
+      '"pattern_obj" must contain at least one cluster column: ',
+      '"cluster" or columns starting with "cutoff"'
+    )
+    return(FALSE)
+  }
+
+  TRUE
+}
+
 #' Make final object for internal use by the app
 #'
 #' This function takes an uploaded object and sanitizes
@@ -508,6 +571,9 @@ make_final_object <- function(obj){
     # get res.list names
     comp.names <- names(obj[[res.name]])
 
+    # these dds objects are not linked to res_list
+    orphan_dds <- NULL
+
     # if res.list contains 'res', 'dds', 'label' elements
     # build the following:
     #
@@ -591,9 +657,8 @@ make_final_object <- function(obj){
         } else if(name %in% names(obj[[res.name]])){
           res <- obj[[res.name]][[name]]
         } else {
-          message('no matching dds object found for ', name, ', skipping\n')
-          obj[[dds.name]] <- obj[[dds.name]][!names(obj[[dds.name]]) %in% name]
-          obj[[rld.name]] <- obj[[rld.name]][!names(obj[[rld.name]]) %in% name]
+          message('no matching dds object found for ', name, '\n')
+          orphan_dds <- c(orphan_dds, name)
           next
         }
 
@@ -658,6 +723,20 @@ make_final_object <- function(obj){
       obj$dds_mapping <- dds_mapping
     }
 
+    # use full idmap for orphan dds objects
+    if(!is.null(orphan_dds)){
+      for(name in orphan_dds){
+        dds <- obj[[dds.name]][[name]]
+        rownames(dds) <- all_idmap[rownames(dds)]
+
+        rld <- obj[[rld.name]][[name]]
+        rownames(rld) <- all_idmap[rownames(rld)]
+
+        obj[[dds.name]][[name]] <- dds
+        obj[[rld.name]][[name]] <- rld
+      }
+    }
+
     # if degpatterns element exists, add symbol column
     if(length(degpatterns.name) != 0){
       obj[[ degpatterns.name ]] <- lapply(obj[[ degpatterns.name ]],
@@ -2485,6 +2564,7 @@ plotScatter.label <- function(compare,
 #' @param alpha float, marker opacity (default=1).
 #' @param size float, marker size (default=4).
 #' @param show.grid string, can be 'yes' (default) or 'no'.
+#' @param source name of source to return event_data from
 
 #' @return plotly handle
 #'
@@ -2567,7 +2647,8 @@ plotScatter.label_ly <- function(compare,
                                  lines=c('yes', 'yes', 'yes'),
                                  alpha=1,
                                  size=4,
-                                 show.grid='yes') {
+                                 show.grid='yes',
+                                 source='A') {
 
   names(color.palette) <- c('None', label_x, label_y, 'Both - opposite LFC sign', 'Both - same LFC sign')
 
@@ -2591,7 +2672,7 @@ plotScatter.label_ly <- function(compare,
 
   show.grid <- if (show.grid == 'yes') TRUE else FALSE
 
-  p <- plot_ly()
+  p <- plot_ly(source=source)
 
   # list of plotting characters
   pch <- c('in'='circle',
@@ -2620,7 +2701,7 @@ plotScatter.label_ly <- function(compare,
       p <- p %>% add_trace(data = df_i[df_i$shape == sym, ],
                            x = ~get(x),
                            y = ~get(y),
-                           type = 'scatter',
+                           type = 'scattergl',
                            mode = 'markers',
                            text = ~get(name.col),
                            hoverinfo = 'text',
@@ -2639,14 +2720,16 @@ plotScatter.label_ly <- function(compare,
     lab.df <- df[df[[name.col]] %in% lab.genes, ]
     if(nrow(lab.df) > 0){
       p <- p %>%
-          add_markers(x=lab.df[[x]], y=lab.df[[y]],
-                      text=lab.df$name.col,
-                      hoverinfo='none',
-                      name='Gene scratchpad',
-                      marker=list(color='black',
-                                  symbol='circle-open',
-                                  size=size*2,
-                                  line=list(width=2)))
+          add_trace(x=lab.df[[x]], y=lab.df[[y]],
+                    text=lab.df$name.col,
+                    hoverinfo='none',
+                    type='scattergl',
+                    mode='markers',
+                    name='Gene scratchpad',
+                    marker=list(color='black',
+                                symbol='circle-open',
+                                size=size*2,
+                                line=list(width=2)))
     }
   }
 
@@ -2670,6 +2753,7 @@ plotScatter.label_ly <- function(compare,
                                   orientation = 'v',
                                   xanchor = 'left',
                                   yanchor = 'middle',
+                                  itemsizing = 'constant',
                                   font = list(size = 14),
                                   title = list(text = 'Significant in:')))
 
@@ -2702,7 +2786,7 @@ plotScatter.label_ly <- function(compare,
 
   # Add all collected shapes at once
   if (length(shapes_to_add) > 0) {
-    p <- p %>% layout(shapes = shapes_to_add)
+    p <- p %>% layout(shapes = shapes_to_add, dragmode='select')
   }
 
   # Return the Plotly plot object
diff --git a/R/imports.R b/R/imports.R
index 155f2ae..53e91a9 100644
--- a/R/imports.R
+++ b/R/imports.R
@@ -19,8 +19,8 @@
 #' @importFrom htmltools withTags tagAppendChild tagAppendChildren tags tagList
 #' @importFrom igraph V "V<-"
 #' @importFrom MatrixGenerics rowVars
-#' @importFrom methods new
-#' @importFrom plotly plotlyOutput renderPlotly layout plot_ly add_trace add_markers toWebGL save_image ggplotly
+#' @importFrom methods new .hasSlot
+#' @importFrom plotly plotlyOutput renderPlotly layout plot_ly add_trace add_markers toWebGL save_image ggplotly plotlyProxy event_data event_register
 #' @importFrom RColorBrewer brewer.pal
 #' @importFrom reticulate py_install use_virtualenv
 #' @importFrom rintrojs introjsUI introBox introjs
diff --git a/R/load-new-data.R b/R/load-new-data.R
index 4f3962e..a620271 100644
--- a/R/load-new-data.R
+++ b/R/load-new-data.R
@@ -42,7 +42,6 @@ NULL
 loadDataUI <- function(id){
   ns <- NS(id)
 
-  # TODO: add multiple dds
   tagList(
     fluidRow(
       column(12, align='left',
@@ -69,6 +68,14 @@ loadDataUI <- function(id){
     textOutput(ns('func_summary')),
     br(), br(),
 
+    span('Step 4: ',
+         style='font-style: italic;'),
+    actionButton(ns('add_dp'), 'Add pattern analysis results'),
+    span('(Optional)',
+         style='font-style: italic;'),
+    textOutput(ns('dp_summary')),
+    br(), br(),
+
     actionButton(ns('create_new'), 'Create data set',
                  class='btn-primary')
   ) # tagList
@@ -767,7 +774,7 @@ loadDataServer <- function(id, username, config, rds=NULL){
 
           # GSEA columns
           cprof_gsea_cols <- c('ID', 'Description', 'core_enrichment', 'setSize',
-                               'pvalue', 'p,adjust', 'qvalue', 'NES', 'setSize')
+                               'pvalue', 'p.adjust', 'qvalue', 'NES', 'setSize')
 
           # check for clusterProfiler columns
           if(all(cprof_or_cols %in% colnames(eres))){
@@ -841,6 +848,211 @@ loadDataServer <- function(id, username, config, rds=NULL){
         removeModal()
       })
 
+      #################### Pattern analysis results ####################
+
+      observeEvent(input$add_dp, {
+        if(is.null(new_obj$dds_list)){
+          showNotification(
+            'Must add at least one counts table before uploading pattern analysis results!',
+            type='error'
+          )
+        }
+
+        validate(
+          need(!is.null(new_obj$dds_list), 'Must have counts')
+        )
+
+        if(is.null(new_obj$res_list)){
+          showNotification(
+            'Must add at least one DE results table before uploading pattern analysis results!',
+            type='error'
+          )
+        }
+
+        validate(
+          need(!is.null(new_obj$res_list), 'Must have DE results')
+        )
+
+        showModal(
+          modalDialog(
+            fileInput(ns('dp_file'),
+                      label='Pattern analysis result file(s)',
+                      multiple=TRUE),
+
+            tags$div(
+              span('*Can add multiple files here'),
+              br(), br(),
+              span('Supported formats:'),
+              tags$ul(
+                tags$li('RDS files containing a degPatterns-like object (data.frame or list with "normalized" data.frame).'),
+                tags$li('Tab-delimited text files (TSV) containing pattern analysis table columns.')
+              ),
+              style='font-style: italic;'
+            ),
+
+            footer=tagList(
+                     actionButton(ns('add_dp_files'), 'OK'),
+                     modalButton('Cancel')
+                   ),
+            easyClose=TRUE
+          )
+        )
+      })
+
+      observeEvent(input$add_dp_files, {
+        if(is.null(input$dp_file)){
+          showNotification(
+            'No pattern analysis results uploaded!',
+            type='error'
+          )
+        }
+
+        req(input$dp_file)
+
+        tag <- tagList(
+                 fluidRow(
+                   column(6, strong('Analysis name')),
+                   column(6, strong('File'))
+                 )
+               )
+
+        for(i in seq_len(nrow(input$dp_file))){
+          tmp_id <- tools::file_path_sans_ext(basename(input$dp_file$name[i]))
+
+          tag <- tagAppendChildren(
+                   tag,
+                   fluidRow(
+                     column(6,
+                       textInput(ns(paste0('dp_id', i)),
+                                 label=NULL,
+                                 value=tmp_id)
+                     ),
+                     column(6,
+                       span(input$dp_file$name[i])
+                     )
+                   )
+                 )
+        }
+
+        tag <- tagAppendChildren(
+                 tag,
+                 tags$div(
+                   tags$ul(
+                     tags$li('Analysis name: Unique name without white-space or commas.'),
+                     tags$li('Each uploaded object must match the expected pattern-analysis schema.')
+                   ),
+                   style='font-style: italic;'
+                 )
+               )
+
+        showModal(
+          modalDialog(
+            tag,
+            footer=tagList(
+                     actionButton(ns('add_dp_do'), 'OK'),
+                     modalButton('Cancel')
+                   ),
+            easyClose=TRUE
+          )
+        )
+      })
+
+      output$dp_summary <- renderText({
+        if(!is.null(new_obj$degpatterns)){
+          nsets <- length(new_obj$degpatterns)
+
+          if(nsets > 1){
+            msg <- paste(nsets, 'pattern analysis results')
+          } else {
+            msg <- paste(nsets, 'pattern analysis result')
+          }
+          msg
+        }
+      })
+
+      observeEvent(input$add_dp_do, {
+        req(input$dp_file)
+
+        ndp <- nrow(input$dp_file)
+        all_names <- paste0('dp_id', seq_len(ndp))
+
+        # check that analysis names are not empty
+        for(name in all_names){
+          if(input[[ name ]] == ''){
+            showNotification(
+              'Pattern analysis name cannot be empty!',
+              type='warning'
+            )
+          }
+
+          validate(
+            need(input[[ name ]] != '', '')
+          )
+
+          if(grepl('[[:space:],]', input[[ name ]])){
+            showNotification(
+              'Pattern analysis name cannot contain white-space or commas!',
+              type='warning'
+            )
+          }
+
+          validate(
+            need(!grepl('[[:space:],]', input[[ name ]]), '')
+          )
+        }
+
+        for(i in seq_len(ndp)){
+          dp_id <- input[[ paste0('dp_id', i) ]]
+          f <- input$dp_file$datapath[i]
+          ext <- tolower(tools::file_ext(input$dp_file$name[i]))
+
+          if(ext == 'rds'){
+            dp_obj <- readRDS(f)
+          } else if(ext %in% c('tsv', 'txt')){
+            dp_obj <- read.table(f, sep='\t', header=TRUE)
+          } else {
+            showNotification(
+              paste0('Unsupported pattern analysis file type: "', ext, '". Use .rds, .tsv or .txt'),
+              type='error'
+            )
+
+            validate(
+              need(ext %in% c('rds', 'tsv', 'txt'), '')
+            )
+          }
+
+          is_valid <- is_valid_pattern_obj(dp_obj, require_symbol=FALSE)
+          if(!is_valid){
+            showNotification(
+              paste0('Invalid pattern analysis object: "', input$dp_file$name[i], '"'),
+              type='error'
+            )
+
+            validate(
+              need(is_valid, '')
+            )
+          }
+
+          if(is.null(new_obj$degpatterns)){
+            new_obj$degpatterns <- setNames(list(dp_obj), dp_id)
+          } else if(dp_id %in% names(new_obj$degpatterns)){
+            showNotification(
+              paste0('Pattern analysis named "', dp_id,
+                     '" already present in object. Please choose different name'),
+              type='error'
+            )
+
+            validate(
+              need(!dp_id %in% names(new_obj$degpatterns), '')
+            )
+          } else {
+            new_obj$degpatterns[[ dp_id ]] <- dp_obj
+          }
+        }
+
+        removeModal()
+      })
+
       #################### save object ####################
 
       observeEvent(input$create_new, {
@@ -954,11 +1166,12 @@ loadDataServer <- function(id, username, config, rds=NULL){
             # - this prevents saved object from becoming very large if another
             #   object has been previously loaded
             combined_final$dds <- lapply(combined_final$dds, function(x){
-                                    attr(x@design, '.Environment') <- NULL
+                                    if(.hasSlot(x, 'design')) attr(x@design, '.Environment') <- NULL
                                     x
                                   })
 
-            attr(combined_final$all_dds@design, '.Environment') <- NULL
+            if(.hasSlot(combined_final$all_dds, 'design'))
+              attr(combined_final$all_dds@design, '.Environment') <- NULL
 
             saveRDS(combined_final, ofile,
                     compress=as.logical(input$compress))
@@ -988,8 +1201,27 @@ loadDataServer <- function(id, username, config, rds=NULL){
               )
             } else {
               if(!input$dir_new %in% y$data_area[[ug]]){
-                y$data_area[[ug]] <- c(y$data_area[[ug]],
-                                       input$dir_new)
+                # check if any parent path of new_dir exists in data_areas
+                # if not, add to list
+                parent <- FALSE
+
+                path <- normalizePath(path.expand(input$dir_new), mustWork=FALSE)
+                current_areas <- normalizePath(path.expand(y$data_area[[ ug ]]), mustWork=FALSE)
+
+                while(TRUE){
+                  if(path %in% current_areas){
+                    parent <- TRUE
+                    break
+                  } else {
+                    path <- dirname(path)
+                    if(path == '.' || path == '/') break
+                  }
+                }
+
+                if(!parent){
+                  y$data_area[[ug]] <- c(y$data_area[[ug]],
+                                         input$dir_new)
+                }
               }
             }
             save_access_yaml(y)
diff --git a/R/pattern-plot.R b/R/pattern-plot.R
index b58e7e2..684af84 100644
--- a/R/pattern-plot.R
+++ b/R/pattern-plot.R
@@ -495,6 +495,8 @@ patternPlotServer <- function(id,
         )
 
         obj <- pattern_obj()[[input$dp_analysis]]
+
+        # if DEGpatterns object, only use 'normalized' slot
         if(!is.data.frame(obj)) obj <- obj$normalized
 
         # get metadata and attach if necessary
diff --git a/R/save_object.R b/R/save_object.R
index aad8189..faea2a6 100644
--- a/R/save_object.R
+++ b/R/save_object.R
@@ -295,11 +295,12 @@ saveServer <- function(id, original, current, coldata, pattern, username, config
             # - this prevents saved object from becoming very large if another
             #   object has been previously loaded
             obj$dds <- lapply(obj$dds, function(x){
-                         attr(x@design, '.Environment') <- NULL
+                         if(.hasSlot(x, 'design')) attr(x@design, '.Environment') <- NULL
                          x
                        })
 
-            attr(obj$all_dds@design, '.Environment') <- NULL
+            if(.hasSlot(obj$all_dds, 'design'))
+              attr(obj$all_dds@design, '.Environment') <- NULL
 
             saveRDS(obj, destpath, compress=as.logical(input$compress))
 
@@ -328,8 +329,27 @@ saveServer <- function(id, original, current, coldata, pattern, username, config
               )
             } else {
               if(!input$rds_path %in% y$data_area[[ug]]){
-                y$data_area[[ug]] <- c(y$data_area[[ug]],
-                                       input$rds_path)
+                # check if any parent path of RDS object exists in data_areas
+                # if not, add to list
+                parent <- FALSE
+
+                path <- normalizePath(dirname(path.expand(input$rds_path)), mustWork=FALSE)
+                current_areas <- normalizePath(path.expand(y$data_area[[ ug ]]), mustWork=FALSE)
+
+                while(TRUE){
+                  if(path %in% current_areas){
+                    parent <- TRUE
+                    break
+                  } else {
+                    path <- dirname(path)
+                    if(path == '.' || path == '/') break
+                  }
+                }
+
+                if(!parent){
+                  y$data_area[[ug]] <- c(y$data_area[[ug]],
+                                         input$rds_path)
+                }
               }
             }
             save_access_yaml(y)
diff --git a/R/scatter-plot.R b/R/scatter-plot.R
index 817490c..48c4990 100644
--- a/R/scatter-plot.R
+++ b/R/scatter-plot.R
@@ -6,8 +6,9 @@
 #' @param id Module id
 #' @param panel string, can be 'sidebar' or 'main' passed to UI
 #' @param obj reactiveValues object containing carnation object passed to server
-#' @param plot_args reactive containing 'fdr.thres' (padj threshold), 'fc.thres' (log2FC) &
-#' 'gene.to.plot' (genes to be labeled) passed to server
+#' @param plot_args reactive containing 'fdr.thres' (padj threshold), 'fc.thres' (log2FC)
+#' @param gene_scratchpad reactive containing gene scratchpad genes
+#' @param reset_genes reactive to reset gene scratchpad selection
 #' @param config reactive list with config settings passed to server
 #'
 #' @returns
@@ -32,11 +33,13 @@
 #' plot_args <- reactive({
 #'   list(
 #'     fdr.thres=0.1,
-#'     fc.thres=0,
-#'     gene.to.plot=c('gene1', 'gene2')
+#'     fc.thres=0
 #'   )
 #' })
 #'
+#' gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+#' reset_genes <- reactiveVal()
+#'
 #' config <- reactiveVal(get_config())
 #'
 #' shinyApp(
@@ -45,7 +48,8 @@
 #'          mainPanel(scatterPlotUI('p', 'sidebar'))
 #'        ),
 #'   server = function(input, output, session){
-#'              scatterPlotServer('p', obj, plot_args, config)
+#'              scatter_data <- scatterPlotServer('p', obj, plot_args,
+#'                                gene_scratchpad, reset_genes, config)
 #'            }
 #' )
 #'
@@ -108,16 +112,6 @@ scatterPlotUI <- function(id, panel){
         ) # column
       ), # fluidRow
 
-      fluidRow(
-        column(6, h5('Show table?')),
-        column(6,
-          selectInput(ns("show_table"), label=NULL,
-                      choices=c('yes', 'no'),
-                      selected='yes'
-          ) # selectInput
-        ) # column
-      ), # fluidRow
-
       wellPanel(
         style='background: white',
 
@@ -285,23 +279,75 @@ scatterPlotUI <- function(id, panel){
         ) # column
       ), # fluidRow
 
-      withSpinner(
-        uiOutput(ns('scatterplot_out'))
-      ), # withSpinner
+      conditionalPanel(paste0('input["', ns('plot_interactive'), '"] == "yes"'),
+        withSpinner(
+          plotlyOutput(ns('plotly_out'), height='600px')
+        )
+      ), # conditionalPanel
+      conditionalPanel(paste0('input["', ns('plot_interactive'), '"] == "no"'),
+        withSpinner(
+          plotOutput(ns('plot_out'), height='600px')
+        )
+      ), # conditionalPanel
 
-      withSpinner(
-        DTOutput(ns('scatter_datatable_out'))
-      ) # withSpinner
+      fluidRow(
+        column(3,
+
+          h4('Selection settings'),
+
+          bsCollapse(open='Plot selection',
+            bsCollapsePanel('Plot selection',
+              fluidRow(style='margin-left: 2px;',
+                uiOutput(ns('pt_selected')),
+                actionButton(ns('filter_sel_do'),
+                             label='Show/Hide in table'),
+                actionButton(ns('reset_plt_selection'),
+                                'Clear',
+                                class='btn-primary')
+              ) # fluidRow
+            ) # bsCollapsePanel
+          ), # bsCollapse
+
+          bsCollapse(open='Table selection',
+            bsCollapsePanel('Table selection',
+              fluidRow(style='margin-left: 2px;',
+                actionButton(ns('add_selected'), 'Add to scratchpad'),
+                actionButton(ns('reset_tbl'),
+                             'Clear selection',
+                             class='btn-primary')
+              ) # fluidRow
+            ) # bsCollapsePanel
+          ), # bsCollapse
+
+          h4('Filter table by significance'),
+          selectizeInput(ns('filter_tbl'), label=NULL, width='100%',
+                         choices=NULL, selected=NULL, multiple=TRUE),
+
+          # For 'Select all' and 'Select none' buttons
+          fluidRow(style='margin-bottom: 5px; margin-left: 2px;',
+            actionButton(ns('select_all'), 'Select all', class = "btn-secondary"),
+            actionButton(ns('select_none'), 'Select none', class = "btn-secondary"),
+            actionButton(ns('filter_tbl_do'),
+                         label='Apply',
+                         icon=icon('filter'),
+                         class='btn-primary')
+          ) # fluidRow
+
+        ), # column
+        column(9, style='margin-top: 10px;',
+          withSpinner(
+            DTOutput(ns('scatter_tbl'))
+          ) # withSpinner
+        ) # column
+      ) # fluidRow
 
-     # conditionalPanel("input.show_table == 'yes'",
-     # ) # conditionalPanel
     ) # tagList
   } # else if panel='main'
 } # scatterPlotUI
 
 #' @rdname scattermod
 #' @export
-scatterPlotServer <- function(id, obj, plot_args, config){
+scatterPlotServer <- function(id, obj, plot_args, gene_scratchpad, reset_genes, config){
 
   moduleServer(
     id,
@@ -332,9 +378,21 @@ scatterPlotServer <- function(id, obj, plot_args, config){
       df_react <- reactiveVal(NULL)
       df_full <- reactiveVal(NULL)
 
+      # reactive to hold plot source
+      plot_source <- reactiveVal(NULL)
+
       # reactive values to keep track of axis limits
       axis_limits <- reactiveValues(lim.x=NULL, lim.y=NULL)
 
+      # reactive to hold labeled genes
+      genes_clicked <- reactiveValues(g=NULL)
+
+      # reactive to hold selected genes
+      selected_genes <- reactiveValues(g=NULL)
+
+      # reactive to toggle table selection by selected genes
+      filter_tbl_by_sel_genes <- reactiveVal(FALSE)
+
       # Initialize comparison selection dropdowns when data is available
       observeEvent(comp_all(), {
         validate(
@@ -351,7 +409,7 @@ scatterPlotServer <- function(id, obj, plot_args, config){
 
         df_react(NULL)
         df_full(NULL)
-        })
+      })
       # -------------------------------------------------------------- #
 
       # --------------- Set FDR and FC thresholds ---------------- #
@@ -369,6 +427,21 @@ scatterPlotServer <- function(id, obj, plot_args, config){
         curr_thres$fdr.thres <- fdr.thres
         curr_thres$fc.thres <- fc.thres
       })
+
+      # gene scratchpad
+
+      observeEvent(gene_scratchpad(), {
+        g <- gene_scratchpad()
+        if(any(g != '')){
+          if(!all(g %in% genes_clicked$g))
+            genes_clicked$g <- unique(c(genes_clicked$g, g))
+        }
+      })
+
+      observeEvent(reset_genes(), {
+        genes_clicked$g <- NULL
+      })
+
       # ------------------------------------------------------------#
 
       # ------------- helper functions -----------------------------#
@@ -424,7 +497,8 @@ scatterPlotServer <- function(id, obj, plot_args, config){
              input$x_axis_comp,
              input$y_axis_comp,
              curr_thres$fc.thres,
-             curr_thres$fdr.thres)
+             curr_thres$fdr.thres,
+             genes_clicked$g)
       }, {
 
         req(app_object()$res)
@@ -552,14 +626,33 @@ scatterPlotServer <- function(id, obj, plot_args, config){
         }
 
         # Significance as factor, to reorder in the graph
-        df$significance <- factor(df$significance, levels = c('None', label_i, label_j, 'Both - opposite LFC sign', 'Both - same LFC sign'))
+        sig_levels <- c('None', label_i, label_j,
+                        'Both - opposite LFC sign', 'Both - same LFC sign')
+        df$significance <- factor(df$significance, levels = sig_levels)
 
         # Store the dataframe in the df_react reactiveVal
+        updateSelectizeInput(session, 'filter_tbl', choices=sig_levels, selected=sig_levels)
+
         df_react(df)
         df_full(df_full)
 
         flags$data_loaded <- flags$data_loaded + 1
       })
+
+      # observers for tbl filters
+      observeEvent(input$select_all, {
+        # Get all possible comparison options
+        all_sig <- levels(df_react()$significance)
+        # Update the select_none checkbox
+        updateSelectizeInput(session, 'filter_tbl', selected=all_sig)
+      })
+
+      # Observer for Select none checkbox
+      observeEvent(input$select_none, {
+        # Update comp_all with no selected comparisons
+        updateSelectizeInput(session, 'filter_tbl', selected=character(0))
+      })
+
       # ---------------------------------------------------------- #
 
       # --------------- Swap comparisons button  ----------------- #
@@ -647,8 +740,7 @@ scatterPlotServer <- function(id, obj, plot_args, config){
         }
 
         # filter rows with NA values
-        df <- df %>% filter(!is.na(.data[[ xcol ]]))
-        df <- df %>% filter(!is.na(.data[[ xcol ]]))
+        df <- df %>% filter(!is.na(.data[[ xcol ]]), !is.na(.data[[ ycol ]]))
 
         # Create column with plotting character based on lim.x
         # Change point values for those outside plot limits to values that are within the limits
@@ -698,7 +790,7 @@ scatterPlotServer <- function(id, obj, plot_args, config){
         )
 
         # Get genes to label
-        genes <- plot_args()$gene.to.plot
+        genes <- genes_clicked$g
         if(is.null(genes) || all(genes %in% '')){
             lab.genes <- NULL
         } else {
@@ -764,7 +856,7 @@ scatterPlotServer <- function(id, obj, plot_args, config){
         lab.genes <- params[['lab.genes']]
         color.palette <- params[['color.palette']]
 
-        plotScatter.label_ly(
+        p <- plotScatter.label_ly(
           compare=input$compare,
           df=df,
           label_x=input$x_axis_comp,
@@ -777,93 +869,230 @@ scatterPlotServer <- function(id, obj, plot_args, config){
           size=input$size,
           show.grid=input$show_grid,
           color.palette=color.palette,
-          lab.genes=lab.genes
+          lab.genes=lab.genes,
+          source='scatter'
         )
 
-     }) # eventReactive scatterplot_ly
+        # save plot source to reactive
+        plot_source('scatter')
+
+        event_register(p, 'plotly_selected')
+
+        p
+      }) # eventReactive scatterplot_ly
       # ----------------------------------------------------- #
 
-      # ---------------------- renerUI ---------------------- #
-      output$scatterplot_out <- renderUI({
-        if (input$plot_interactive == 'yes') {
+      output$plotly_out <- renderPlotly({
+        scatterplot_ly()
+      })
 
-          p <- scatterplot_ly() %>% toWebGL()
+      output$plot_out <- renderPlot({
+        scatterplot() + theme(text=element_text(size=18))
+      })
 
-          output$plot1 <- renderPlotly({ p })
+      #################### point selection ####################
 
-          withSpinner(
-            plotlyOutput(ns('plot1'), height='600px')
-          )
+      plotProxy <- plotlyProxy('plotly_out', session)
+
+      get_pt_selected <- reactive({
+        req(plot_source())
+        event_data('plotly_selected', source=plot_source())
+      })
 
-        } else if (input$plot_interactive == 'no') {
+      observeEvent(get_pt_selected(), {
+        df <- get_pt_selected()
 
-          p <- scatterplot() + theme(text=element_text(size=18))
+        data_df <- df_full()
+        xcol <- paste0(input$compare, '.x')
+        ycol <- paste0(input$compare, '.y')
 
-          output$plot2 <- renderPlot({ p })
+        # get points by matching coords & key
+        keys <- paste(df$x, df$y)
+        data_keys <- paste(data_df[, xcol], data_df[, ycol])
 
-          withSpinner(
-            plotOutput(ns('plot2'), height='600px')
+        new <- data_df$geneid[data_keys %in% keys]
+        curr <- unique(unlist(selected_genes$g))
+
+        # only add new points
+        if(!all(new %in% curr)){
+          new_idx <- which(!new %in% curr)
+          showNotification(
+              paste0('Adding ', length(new_idx), ' genes to selection')
+          )
+
+          selected_genes$g[[ length(selected_genes$g) + 1 ]] <- new[new_idx]
+        } else if(length(new) > 0){
+          showNotification(
+              paste0('All selected genes already in selection'),
+              type='warning'
           )
         }
-      }) # renderUI
+      })
+
+      output$pt_selected <- renderUI({
+        np <- length(unique(unlist(selected_genes$g)))
+
+        tagList(
+          fluidRow(
+            column(12, style='margin-bottom: 10px;',
+
+              paste(np, 'genes selected')
+            )
+          )
+        )
+      })
+
+      observeEvent(input$reset_plt_selection, {
+        selected_genes$g <- NULL
+      })
+
+      observeEvent(input$filter_sel_do, {
+        filter_tbl_by_sel_genes(!filter_tbl_by_sel_genes())
+      })
+
       # ------------------------------------------------------- #
 
       # -------------------- renerDataTable  ------------------ #
-      # Optionally display datatable for scatter plot input data
-      output$scatter_datatable_out <- renderDT({
-        if (input$show_table == 'yes') {
-          validate(
-            need(!is.null(df_full()), '')
-          )
-          df <- df_full()
+      scatter_dt <- eventReactive(c(df_react(), input$x_axis_comp, input$y_axis_comp,
+                                    input$filter_tbl_do, filter_tbl_by_sel_genes()), {
+        validate(
+          need(!is.null(df_full()), '')
+        )
+        df <- df_full()
 
-          # move geneid to beginning to work with container
-          df <- df %>% relocate('geneid')
+        # add significance column
+        sig_df <- df_react()
 
-          # Define the columns to format to 3 sig figs
-          columns_to_format <- c("padj.x", "padj.y", "log2FoldChange.x", "log2FoldChange.y")
-          which_cols <- which(colnames(df) %in% columns_to_format)
-          border_cols <- c(1, grep('padj', colnames(df)))
+        # map geneid to significance
+        sigvec <- sig_df$significance
+        names(sigvec) <- sig_df$geneid
+        df$significance <- sigvec[df$geneid]
 
-          all_comps <- c(input$x_axis_comp, input$y_axis_comp)
-          validate(
-            need(!any(is.null(all_comps)), 'Waiting for selection')
+        if(filter_tbl_by_sel_genes()){
+          idx <- df$geneid %in% unique(unlist(selected_genes$g))
+
+          if(sum(idx) == 0){
+            showNotification(
+              'No rows left in table after filtering', type='error'
+            )
+
+            validate(need(sum(idx) > 0, ''))
+          }
+          df <- df[idx,]
+        }
+
+        # get current filters
+        curr_filters <- input$filter_tbl
+        idx <- df$significance %in% curr_filters
+        if(sum(idx) == 0){
+          showNotification(
+            'No rows left in table after filtering', type='error'
           )
 
-          # build container for table
-          sketch <- htmltools::withTags(table(
-            class = 'display',
-            tags$thead(
-              tags$tr(
-                tags$th(rowspan=2, 'geneid'),
-                lapply(all_comps,
-                       function(x) tags$th(class='dt-center', colspan=2, x))
-              ),
-              tags$tr(
-                lapply(rep(c('log2FoldChange', 'padj'), 2), tags$th)
-              )
+          validate(need(sum(idx) > 0, ''))
+        }
+        # move geneid & significance to beginning to work with container
+        df[which(idx),] %>% relocate('significance') %>% relocate('geneid')
+
+      })
+
+      # Optionally display datatable for scatter plot input data
+      output$scatter_tbl <- renderDT({
+        validate(
+          need(!is.null(scatter_dt()), '')
+        )
+        df <- scatter_dt()
+
+        # Define the columns to format to 3 sig figs
+        columns_to_format <- c("padj.x", "padj.y", "log2FoldChange.x", "log2FoldChange.y")
+        which_cols <- which(colnames(df) %in% columns_to_format)
+        border_cols <- c(1, 2, grep('padj', colnames(df)))
+
+        all_comps <- c(input$x_axis_comp, input$y_axis_comp)
+        validate(
+          need(!any(is.null(all_comps)), 'Waiting for selection')
+        )
+
+        # build container for table
+        sketch <- htmltools::withTags(table(
+          class = 'display',
+          tags$thead(
+            tags$tr(
+              lapply(c('geneid', 'significance'), function(x) tags$th(rowspan=2, x)),
+              lapply(all_comps,
+                     function(x) tags$th(class='dt-center', colspan=2, x))
+            ),
+            tags$tr(
+              lapply(rep(c('log2FoldChange', 'padj'), 2), tags$th)
             )
-          ))
-
-          df %>%
-            datatable(rownames=FALSE,
-                      selection='none',
-                      container=sketch,
-                      options=list(autoWidth=TRUE,
-                                   columnDefs=list(list(className='dt-center',
-                                                        targets=seq_len((ncol(df)-1)))))) %>%
-            formatStyle(columns=border_cols,
-                        'border-right'='solid 1px') %>%
-            formatSignif(columns=which_cols, digits=5)
-        } # if show_table == 'yes'
+          )
+        ))
+
+        df %>%
+          datatable(rownames=FALSE,
+                    selection=list(mode='multiple'),
+                    container=sketch,
+                    options=list(autoWidth=TRUE,
+                                 columnDefs=list(list(className='dt-center',
+                                                      targets=seq_len((ncol(df)-1)))))) %>%
+          formatStyle(columns=border_cols,
+                      'border-right'='solid 1px') %>%
+          formatSignif(columns=which_cols, digits=5)
       }) # renderDT
       # ------------------------------------------------------- #
 
+      # table selection handling
+
+      scatter_proxy <- dataTableProxy('scatter_tbl')
+
+      observeEvent(input$reset_tbl, {
+        scatter_proxy %>% selectRows(NULL)
+      })
+
+      observeEvent(input$add_selected, {
+        tbl <- scatter_dt()
+        sel <- input$scatter_tbl_rows_selected
+
+        # handle NAs in symbol
+        s <- tbl$geneid
+        #s[is.na(s)] <- tbl$gene[is.na(s)]
+
+        if(is.null(sel)){
+          showNotification(
+            'Cannot add genes, no rows selected', type='warning'
+          )
+          validate(
+            need(!is.null(sel), '')
+          )
+        } else if(all(s[sel] %in% genes_clicked$g)){
+          showNotification(
+            'Selected genes already present in scratchpad, skipping', type='warning'
+          )
+        } else {
+          if(is.null(genes_clicked$g)) selected <- s[sel]
+          else selected <- unique(c(genes_clicked$g, s[sel]))
+
+          new_genes <- setdiff(selected, genes_clicked$g)
+          showNotification(
+            paste('Adding', length(new_genes),
+                  'new genes to scratchpad')
+          )
+
+          genes_clicked$g <- c(genes_clicked$g, new_genes)
+        }
+      }) # observeEvent
+
       # ---------------- Help and download buttons ------------ #
       helpButtonServer('de_cmp_scatter_help', size='l')
       helpButtonServer('de_scatter_help', size='l')
       downloadButtonServer('scatterplot_download', scatterplot, 'scatterplot')
       # ----------------------------------------------------- #
+
+      return(
+        reactive({
+          list(genes=genes_clicked$g)
+        })
+      )
     } # Server function
   ) # moduleServer
 } # maPlotServer
diff --git a/README.md b/README.md
index 374c4b4..c5d2452 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,19 @@
 # Carnation
 
+[![](https://bioconductor.org/shields/availability/devel/carnation.svg)](https://bioconductor.org/packages/devel/bioc/html/carnation.html#archives)
+[![](https://bioconductor.org/shields/lastcommit/devel/bioc/carnation.svg)](https://bioconductor.org/checkResults/devel/bioc-LATEST/carnation/)
+[![](https://bioconductor.org/shields/build/devel/bioc/carnation.svg)](https://bioconductor.org/checkResults/devel/bioc-LATEST/carnation/)
+[![](https://bioconductor.org/shields/years-in-bioc/carnation.svg)](https://bioconductor.org/packages/devel/bioc/html/carnation.html#since)
+
 **Deeply explore your bulk RNA-Seq data with interactive visualizations**
 
 Carnation is an interactive Shiny dashboard that transforms complex bulk RNA-Seq data into beautiful, insightful visualizations. Designed for both computational and experimental biologists, Carnation makes exploring differential expression analysis, functional enrichment, and pattern analysis intuitive and exciting.
 
+**Carnation is now on Bioconductor devel (Official release: April 2026)**
+
+Check out the official bioconductor page [here](https://bioconductor.org/packages/devel/bioc/html/carnation.html)
+for more details.
+
 ## ✨ Key Features
 
 - **Interactive Visualizations**: Explore your data through multiple perspectives
@@ -23,6 +33,24 @@ Carnation is an interactive Shiny dashboard that transforms complex bulk RNA-Seq
 
 ## 🚀 Installation
 
+Carnation can be installed using `BiocManager::install`. First, start R (version: 4.6)
+and then run:
+
+```r
+# first check to see if BiocManager is available
+if(!requireNamespace('BiocManager', quietly=TRUE)){
+  install.packages('BiocManager')
+}
+
+BiocManager::install('carnation')
+```
+
+To install the 'devel' version
+
+```r
+BiocManager::install('carnation', version='devel')
+```
+
 ### remotes
 
 You can install the developmental version of carnation from github using the `remotes`
@@ -46,11 +74,16 @@ conda activate ./env
 R
 ```
 
-Then install the package with the `remotes` package. Note, here we set `upgrade='never'`
-to make sure the conda-installed package versions remain unchanged.
+Then install the package with the `remotes` package.
+
+Note:
+
+- Conda packages for R >= 4.6.0 may not be available yet causing installation using the default
+  github branch to fail. To avoid this, use branch `r4.3` which pins R to a lower version.
+- Here we set `upgrade='never'` to make sure the conda-installed package versions remain unchanged.
 
 ```r
-remotes::install_github('NICHD-BSPC/carnation', upgrade='never')
+remotes::install_github('NICHD-BSPC/carnation@r4.3', upgrade='never')
 ```
 
 ## 🏁 Getting Started
@@ -124,26 +157,3 @@ We welcome contributions to Carnation! Please feel free to submit issues or pull
 
 Carnation is available under the MIT license.
 
-## 💻 Server Mode
-
-Carnation supports multi-user environments with authentication:
-
-```r
-# Create user database
-credentials <- data.frame(
-  user = c('shinymanager'),
-  password = c('12345'),
-  admin = c(TRUE),
-  stringsAsFactors = FALSE
-)
-
-# Initialize the database
-shinymanager::create_db(
-  credentials_data = credentials,
-  sqlite_path = 'credentials.sqlite',
-  passphrase = 'admin_passphrase'
-)
-
-# Run with authentication
-run_carnation(credentials='credentials.sqlite', passphrase='admin_passphrase')
-```
diff --git a/inst/extdata/config.yaml b/inst/extdata/config.yaml
index 545df0a..6cdffeb 100644
--- a/inst/extdata/config.yaml
+++ b/inst/extdata/config.yaml
@@ -37,6 +37,16 @@ style:
       margin-bottom: -5px
     }
 
+    .div-stats-card {
+      border-radius: 8px;
+      box-shadow: 3px 4px 5px 0px rgba(0, 0, 0, 0.3);
+      margin-bottom: 10px;
+      padding-left: 10px;
+      padding-top: 10px;
+      padding-bottom: 10px;
+      background-color: #ebecf0;
+    }
+
     .rank-list-container.custom-sortable {
       background-color: #d0d0d0;
       width: fit-content;
@@ -202,6 +212,25 @@ server:
     - sizeFactor
 
   de_analysis:
+    column_names:
+      # here we list alternative names of columns
+      # to support multiple tools
+      pvalue:
+        - pvalue #DESeq2
+        - PValue # edgeR
+        - P.Value # limma
+      padj:
+        - padj # DESeq2
+        - FDR # edgeR
+        - adj.P.Val # limma
+      log2FoldChange:
+        - log2FoldChange # DESeq2
+        - logFC # edgeR/limma
+      baseMean:
+        - baseMean # DESeq2
+        - logCPM # edgeR
+        - AveExpr # limma
+
     pdf:
       width: 10
       height: 10
diff --git a/man/carnation-package.Rd b/man/carnation-package.Rd
index 832c6d8..58f4818 100644
--- a/man/carnation-package.Rd
+++ b/man/carnation-package.Rd
@@ -36,6 +36,7 @@ Useful links:
 
 Other contributors:
 \itemize{
+  \item Matthew Tyler Menold \email{matthew.menold@gmail.com} (\href{https://orcid.org/0009-0007-4728-2470}{ORCID}) [contributor]
   \item Ryan Dale \email{ryan.dale@nih.gov} (\href{https://orcid.org/0000-0003-2664-3744}{ORCID}) [funder]
 }
 
diff --git a/man/is_valid_pattern_obj.Rd b/man/is_valid_pattern_obj.Rd
new file mode 100644
index 0000000..83c8ec3
--- /dev/null
+++ b/man/is_valid_pattern_obj.Rd
@@ -0,0 +1,29 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/functions.R
+\name{is_valid_pattern_obj}
+\alias{is_valid_pattern_obj}
+\title{Validate Pattern Analysis Object Schema}
+\usage{
+is_valid_pattern_obj(pattern_obj, require_symbol = FALSE)
+}
+\arguments{
+\item{pattern_obj}{A single pattern analysis element. Must be either a
+\code{data.frame} or a list containing a \code{normalized} \code{data.frame}.}
+
+\item{require_symbol}{Logical, if \code{TRUE} require a \code{symbol} column in the
+analysis table.}
+}
+\value{
+Returns \code{TRUE} when validation succeeds, otherwise returns \code{FALSE}
+after emitting a message describing the issue.
+}
+\description{
+Validate the schema for a single \code{degpatterns} analysis element used by the
+pattern analysis module.
+}
+\examples{
+data(degpatterns_dex, package = "carnation")
+
+is_valid_pattern_obj(degpatterns_dex)
+
+}
diff --git a/man/plotScatter.label_ly.Rd b/man/plotScatter.label_ly.Rd
index c51898f..07fb5b6 100644
--- a/man/plotScatter.label_ly.Rd
+++ b/man/plotScatter.label_ly.Rd
@@ -17,7 +17,8 @@ plotScatter.label_ly(
   lines = c("yes", "yes", "yes"),
   alpha = 1,
   size = 4,
-  show.grid = "yes"
+  show.grid = "yes",
+  source = "A"
 )
 }
 \arguments{
@@ -49,6 +50,8 @@ x = 0 & y = 0, but not the x = y diagonal.}
 \item{size}{float, marker size (default=4).}
 
 \item{show.grid}{string, can be 'yes' (default) or 'no'.}
+
+\item{source}{name of source to return event_data from}
 }
 \value{
 plotly handle
diff --git a/man/scattermod.Rd b/man/scattermod.Rd
index 202ec5d..05a785a 100644
--- a/man/scattermod.Rd
+++ b/man/scattermod.Rd
@@ -8,7 +8,7 @@
 \usage{
 scatterPlotUI(id, panel)
 
-scatterPlotServer(id, obj, plot_args, config)
+scatterPlotServer(id, obj, plot_args, gene_scratchpad, reset_genes, config)
 }
 \arguments{
 \item{id}{Module id}
@@ -17,8 +17,11 @@ scatterPlotServer(id, obj, plot_args, config)
 
 \item{obj}{reactiveValues object containing carnation object passed to server}
 
-\item{plot_args}{reactive containing 'fdr.thres' (padj threshold), 'fc.thres' (log2FC) &
-'gene.to.plot' (genes to be labeled) passed to server}
+\item{plot_args}{reactive containing 'fdr.thres' (padj threshold), 'fc.thres' (log2FC)}
+
+\item{gene_scratchpad}{reactive containing gene scratchpad genes}
+
+\item{reset_genes}{reactive to reset gene scratchpad selection}
 
 \item{config}{reactive list with config settings passed to server}
 }
@@ -48,11 +51,13 @@ obj <- reactiveValues(
 plot_args <- reactive({
   list(
     fdr.thres=0.1,
-    fc.thres=0,
-    gene.to.plot=c('gene1', 'gene2')
+    fc.thres=0
   )
 })
 
+gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+reset_genes <- reactiveVal()
+
 config <- reactiveVal(get_config())
 
 shinyApp(
@@ -61,7 +66,8 @@ shinyApp(
          mainPanel(scatterPlotUI('p', 'sidebar'))
        ),
   server = function(input, output, session){
-             scatterPlotServer('p', obj, plot_args, config)
+             scatter_data <- scatterPlotServer('p', obj, plot_args,
+                               gene_scratchpad, reset_genes, config)
            }
 )
 \dontshow{\}) # examplesIf}
diff --git a/tests/testthat/test-scatter-plot-module.R b/tests/testthat/test-scatter-plot-module.R
index b7ce10c..582991f 100644
--- a/tests/testthat/test-scatter-plot-module.R
+++ b/tests/testthat/test-scatter-plot-module.R
@@ -32,12 +32,16 @@ test_that("scatterPlotServer processes data correctly with log2FoldChange", {
     )
   })
 
+  gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+  reset_genes <- reactiveVal()
   config <- reactiveVal(get_config())
 
   testServer(scatterPlotServer, args = list(
     id = "test_scatter",
     obj = obj,
     plot_args = plot_args,
+    gene_scratchpad = gene_scratchpad,
+    reset_genes = reset_genes,
     config = config
   ), {
     # Set inputs for scatter plot
@@ -109,12 +113,16 @@ test_that("scatterPlotServer handles comparison swapping", {
     )
   })
 
+  gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+  reset_genes <- reactiveVal()
   config <- reactiveVal(get_config())
 
   testServer(scatterPlotServer, args = list(
     id = "test_scatter_swap",
     obj = obj,
     plot_args = plot_args,
+    gene_scratchpad = gene_scratchpad,
+    reset_genes = reset_genes,
     config = config
   ), {
     # Set initial inputs
@@ -174,12 +182,16 @@ test_that("scatterPlotServer handles autoscaling", {
     )
   })
 
+  gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+  reset_genes <- reactiveVal()
   config <- reactiveVal(get_config())
 
   testServer(scatterPlotServer, args = list(
     id = "test_scatter_autoscale",
     obj = obj,
     plot_args = plot_args,
+    gene_scratchpad = gene_scratchpad,
+    reset_genes = reset_genes,
     config = config
   ), {
     # Set inputs
@@ -245,12 +257,16 @@ test_that("scatterPlotServer handles gene labeling", {
     )
   })
 
+  gene_scratchpad <- reactive({ c('gene1', 'gene2') })
+  reset_genes <- reactiveVal()
   config <- reactiveVal(get_config())
 
   testServer(scatterPlotServer, args = list(
     id = "test_scatter_labels",
     obj = obj,
     plot_args = plot_args,
+    gene_scratchpad = gene_scratchpad,
+    reset_genes = reset_genes,
     config = config
   ), {
     # Set inputs