From 30c2e0452acaeb235ad7ec68df2fcc6e2c8e77e6 Mon Sep 17 00:00:00 2001
From: zhanghao-njmu <542370159@qq.com>
Date: Wed, 8 Nov 2023 22:05:45 +0800
Subject: [PATCH 1/4] Update the SCExplorer

---
 R/SCP-analysis.R       |  2 +-
 R/SCP-app.R            | 84 ++++++++++++++++++++++--------------------
 R/SCP-plot.R           | 17 +++++----
 R/SCP-workflow.R       |  2 +
 R/utils.R              |  4 +-
 man/FeatureDimPlot.Rd  |  2 +-
 man/FeatureStatPlot.Rd |  3 ++
 man/GroupHeatmap.Rd    |  2 +-
 man/RunSCExplorer.Rd   |  1 +
 9 files changed, 65 insertions(+), 52 deletions(-)

diff --git a/R/SCP-analysis.R b/R/SCP-analysis.R
index 433a6e0b..28373c27 100644
--- a/R/SCP-analysis.R
+++ b/R/SCP-analysis.R
@@ -5567,7 +5567,7 @@ RunSCVELO <- function(srt = NULL, assay_X = "RNA", slot_X = "counts", assay_laye
     stop("One of 'srt', 'adata' must be provided.")
   }
   if (is.null(group_by)) {
-    stop("'roup_by' must be provided.")
+    stop("'group_by' must be provided.")
   }
   if (is.null(linear_reduction) && is.null(nonlinear_reduction)) {
     stop("'linear_reduction' or 'nonlinear_reduction' must be provided at least one.")
diff --git a/R/SCP-app.R b/R/SCP-app.R
index 6750d394..b30c405f 100644
--- a/R/SCP-app.R
+++ b/R/SCP-app.R
@@ -140,11 +140,10 @@ CreateMetaFile <- function(srt, MetaFile, name = NULL, write_tools = FALSE, writ
     } else {
       write.attributes <- FALSE
     }
-    if (inherits(meta, "numeric")) {
+    if (is.numeric(meta)) {
       meta <- as.double(meta)
       meta_asfeatures <- c(meta_asfeatures, var)
-    }
-    if (!is.numeric(meta)) {
+    } else {
       if (length(unique(meta)) > ignore_nlevel) {
         warning("The number of categories in ", var, " is greater than ", ignore_nlevel, ", it will be ignored.", immediate. = TRUE)
       } else {
@@ -249,7 +248,7 @@ PrepareSCExplorer <- function(object,
                               assays = "RNA", slots = c("counts", "data"),
                               ignore_nlevel = 100, write_tools = FALSE, write_misc = FALSE,
                               compression_level = 6, overwrite = FALSE) {
-  base_dir <- normalizePath(base_dir)
+  base_dir <- normalizePath(base_dir, mustWork = FALSE)
   if (!dir.exists(base_dir)) {
     message("Create SCExplorer base directory: ", base_dir)
     dir.create(base_dir, recursive = TRUE, showWarnings = FALSE)
@@ -585,6 +584,7 @@ RunSCExplorer <- function(base_dir = "SCExplorer",
                           initial_size = 4,
                           initial_ncol = 3,
                           initial_arrange = "Row",
+                          initial_raster = "No",
                           session_workers = 2,
                           plotting_workers = 8,
                           create_script = TRUE,
@@ -653,7 +653,6 @@ if (is.null(initial_group)) {
 if (is.null(initial_feature)) {
   initial_feature <- meta_features_name[1]
 }
-initial_raster <- ifelse(nrow(data) > 1e5, "Yes", "No")
 
 palette_list <- SCP::palette_list
 theme_list <- list(
@@ -892,7 +891,7 @@ ui <- fluidPage(
           ),
           fluidRow(
             column(
-              width = 6, align = "center",
+              width = 4, align = "center",
               radioButtons(
                 inputId = "coExp2",
                 label = "Co-expression",
@@ -902,7 +901,17 @@ ui <- fluidPage(
               ),
             ),
             column(
-              width = 6, align = "center",
+              width = 4, align = "center",
+              radioButtons(
+                inputId = "scale2",
+                label = "Color scale",
+                choices = list("feature" = "feature", "all" = "all"),
+                selected = "feature",
+                inline = TRUE
+              ),
+            ),
+            column(
+              width = 4, align = "center",
               radioButtons(
                 inputId = "raster2",
                 label = "Raster",
@@ -1505,70 +1514,70 @@ server <- function(input, output, session) {
     }
   }
 
-  updateSelectizeInput(session, "features2", choices = c(meta_features_name, all_features), selected = initial_feature, server = TRUE)
-  updateSelectizeInput(session, "features4", choices = c(meta_features_name, all_features), selected = initial_feature, server = TRUE)
-
   # change dataset  ----------------------------------------------------------------
   observe({
     meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset1, "/metadata.stat/asgroups"))
     reduction_name <- meta_struc[meta_struc$group == paste0("/", input$dataset1, "/reductions"), "name"]
     default_reduction <- as.character(rhdf5::h5read(MetaFile, name = paste0("/", input$dataset1, "/reductions.stat/Default_reduction")))
     all_cells <- rhdf5::h5read(DataFile, name = paste0("/", input$dataset1, "/cells"))
-    updateSelectInput(session, "reduction1", choices = reduction_name, selected = default_reduction)
-    updateSelectInput(session, "group1", choices = meta_groups_name, selected = "orig.ident")
+    updateSelectInput(session, "reduction1", choices = reduction_name, selected = intersect(c(initial_reduction, default_reduction), reduction_name)[1])
+    updateSelectInput(session, "group1", choices = meta_groups_name, selected = intersect(c(initial_group, "orig.ident"), meta_groups_name)[1])
     updateSelectInput(session, "split1", choices = c("None", meta_groups_name), selected = "None")
-    updateRadioButtons(session, "raster1", choices = c("Yes", "No"), selected = ifelse(length(all_cells) > 1e5, "Yes", "No"))
-  }) %>% bindEvent(input$dataset1, ignoreNULL = TRUE, ignoreInit = TRUE)
+    updateRadioButtons(session, "raster1", choices = c("Yes", "No"), selected = initial_raster)
+  }) %>% bindEvent(input$dataset1, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
     assays <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset2, data_group)], "/"), function(x) x[3])))
     slots <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset2, data_group)], "/"), function(x) x[4])))
     default_assay <- as.character(rhdf5::h5read(DataFile, name = paste0("/", input$dataset2, "/Default_assay")))
     default_slot <- ifelse("data" %in% slots, "data", slots[1])
-    updateSelectInput(session, "assays2", choices = assays, selected = default_assay)
-    updateSelectInput(session, "slots2", choices = slots, selected = default_slot)
-    data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", input$dataset2, "/", default_assay, "/", default_slot))
+    assay <- intersect(c(initial_assay, default_assay), assays)[1]
+    slot <- intersect(c(initial_slot, default_slot), slots)[1]
+    updateSelectInput(session, "assays2", choices = assays, selected = assay)
+    updateSelectInput(session, "slots2", choices = slots, selected = slot)
+    data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", input$dataset2, "/", assay, "/", slot))
     all_features <- colnames(data)
     all_cells <- rhdf5::h5read(DataFile, name = paste0("/", input$dataset2, "/cells"))
     meta_features_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/metadata.stat/asfeatures"))
     meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/metadata.stat/asgroups"))
     reduction_name <- meta_struc[meta_struc$group == paste0("/", input$dataset2, "/reductions"), "name"]
     default_reduction <- as.character(rhdf5::h5read(MetaFile, name = paste0("/", input$dataset2, "/reductions.stat/Default_reduction")))
-    updateSelectInput(session, "reduction2", choices = reduction_name, selected = default_reduction)
+    updateSelectInput(session, "reduction2", choices = reduction_name, selected = intersect(c(initial_reduction, default_reduction), reduction_name)[1])
     updateSelectizeInput(session, "features2",
-      choices = c(meta_features_name, all_features), selected = meta_features_name[1],
+      choices = c(meta_features_name, all_features), selected = intersect(c(initial_feature, meta_features_name[1]), c(all_features, meta_features_name))[1],
       options = list(maxOptions = 20, maxItems = 20), server = TRUE
     )
     updateSelectInput(session, "split2", choices = c("None", meta_groups_name), selected = "None")
-    updateSelectInput(session, "group2", choices = meta_groups_name, selected = "orig.ident")
-    updateRadioButtons(session, "raster2", choices = c("Yes", "No"), selected = ifelse(length(all_cells) > 1e5, "Yes", "No"))
-  }) %>% bindEvent(input$dataset2, ignoreNULL = TRUE, ignoreInit = TRUE)
+    updateRadioButtons(session, "raster2", choices = c("Yes", "No"), selected = initial_raster)
+  }) %>% bindEvent(input$dataset2, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
     meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset3, "/metadata.stat/asgroups"))
     updateSelectInput(session, "stat3", choices = meta_groups_name, selected = "orig.ident")
-    updateSelectInput(session, "group3", choices = meta_groups_name, selected = "orig.ident")
+    updateSelectInput(session, "group3", choices = meta_groups_name, selected = intersect(c(initial_group, "orig.ident"), meta_groups_name)[1])
     updateSelectInput(session, "split3", choices = c("None", meta_groups_name), selected = "None")
-  }) %>% bindEvent(input$dataset3, ignoreNULL = TRUE, ignoreInit = TRUE)
+  }) %>% bindEvent(input$dataset3, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
     assays <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset4, data_group)], "/"), function(x) x[3])))
     slots <- unique(na.omit(sapply(strsplit(data_group[grep(input$dataset4, data_group)], "/"), function(x) x[4])))
     default_assay <- as.character(rhdf5::h5read(DataFile, name = paste0("/", input$dataset4, "/Default_assay")))
     default_slot <- ifelse("data" %in% slots, "data", slots[1])
-    updateSelectInput(session, "assays4", choices = assays, selected = default_assay)
-    updateSelectInput(session, "slots4", choices = slots, selected = default_slot)
-    data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", input$dataset4, "/", default_assay, "/", default_slot))
+    assay <- intersect(c(initial_assay, default_assay), assays)[1]
+    slot <- intersect(c(initial_slot, default_slot), slots)[1]
+    updateSelectInput(session, "assays4", choices = assays, selected = assay)
+    updateSelectInput(session, "slots4", choices = slots, selected = slot)
+    data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", input$dataset4, "/", assay, "/", slot))
     all_features <- colnames(data)
     meta_features_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset4, "/metadata.stat/asfeatures"))
     meta_groups_name <- rhdf5::h5read(MetaFile, name = paste0("/", input$dataset4, "/metadata.stat/asgroups"))
     updateSelectizeInput(session, "features4",
-      choices = c(meta_features_name, all_features), selected = meta_features_name[1],
+      choices = c(meta_features_name, all_features), selected = intersect(c(initial_feature, meta_features_name[1]), c(all_features, meta_features_name))[1],
       options = list(maxOptions = 20, maxItems = 20), server = TRUE
     )
     updateSelectInput(session, "split4", choices = c("None", meta_groups_name), selected = "None")
-    updateSelectInput(session, "group4", choices = meta_groups_name, selected = "orig.ident")
-  }) %>% bindEvent(input$dataset4, ignoreNULL = TRUE, ignoreInit = TRUE)
+    updateSelectInput(session, "group4", choices = meta_groups_name, selected = intersect(c(initial_group, "orig.ident"), meta_groups_name)[1])
+  }) %>% bindEvent(input$dataset4, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
     if (input$group3 != "None") {
@@ -1747,6 +1756,7 @@ server <- function(input, output, session) {
     features2 <- input$features2
     feature_area2 <- input$feature_area2
     coExp2 <- input$coExp2 == "Yes"
+    scale2 <- input$scale2
     raster2 <- input$raster2 == "Yes"
     palette2 <- input$palette2
     theme2 <- input$theme2
@@ -1765,7 +1775,7 @@ server <- function(input, output, session) {
     features2 <- c(as.character(features2), as.character(feature_area2))
     features2 <- unique(features2[features2 %in% c(all_features, meta_features_name)])
     if (length(features2) == 0) {
-      features2 <- meta_features_name[1]
+      features2 <- intersect(c(initial_feature, meta_features_name[1]), c(all_features, meta_features_name))[1]
     }
 
     promisedData[["p2_dim"]] <- NULL
@@ -1788,7 +1798,7 @@ server <- function(input, output, session) {
         # print(system.time(
         p2_dim <- SCP::FeatureDimPlot(
           srt = srt_tmp, features = features2, split.by = split2, reduction = reduction2, slot = "data", raster = raster2, pt.size = pt_size2,
-          calculate_coexp = coExp2, palette = palette2, theme_use = theme2,
+          calculate_coexp = coExp2, keep_scale = scale2, palette = palette2, theme_use = theme2,
           ncol = ncol2, byrow = byrow2, force = TRUE
         )
         # ))
@@ -1815,7 +1825,7 @@ server <- function(input, output, session) {
     bindCache(
       input$dataset2, input$reduction2, input$split2, input$assays2, input$slots2,
       input$features2, input$feature_area2,
-      input$palette2, input$theme2, input$coExp2, input$raster2,
+      input$palette2, input$theme2, input$coExp2, input$scale2, input$raster2,
       input$pt_size2, input$size2, input$ncol2, input$arrange2
     ) %>%
     bindEvent(input$submit2, ignoreNULL = FALSE, ignoreInit = FALSE)
@@ -2085,7 +2095,7 @@ server <- function(input, output, session) {
     features4 <- c(as.character(features4), as.character(feature_area4))
     features4 <- unique(features4[features4 %in% c(all_features, meta_features_name)])
     if (length(features4) == 0) {
-      features4 <- meta_features_name[1]
+      features4 <- intersect(c(initial_feature, meta_features_name[1]), c(all_features, meta_features_name))[1]
     }
 
     promisedData[["p4"]] <- NULL
@@ -2232,6 +2242,7 @@ server <- function(input, output, session) {
     "library(promises)",
     "library(BiocParallel)",
     "library(ggplot2)",
+    "library(rlang)",
     args_code,
     "plan(multisession, workers = session_workers)",
     "if (.Platform$OS.type == 'windows') {
@@ -2245,11 +2256,6 @@ server <- function(input, output, session) {
   )
   temp <- tempfile("SCExplorer")
   writeLines(app_code, temp)
-  wd <- getwd()
-  on.exit(setwd(wd))
-  setwd(base_dir)
-  source(temp)
-  setwd(wd)
   if (isTRUE(create_script)) {
     app_file <- paste0(base_dir, "/app.R")
     if (!file.exists(app_file) || isTRUE(overwrite)) {
diff --git a/R/SCP-plot.R b/R/SCP-plot.R
index b47b7007..ce1d9c5e 100644
--- a/R/SCP-plot.R
+++ b/R/SCP-plot.R
@@ -1982,7 +1982,7 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
                            show_stat = ifelse(identical(theme_use, "theme_blank"), FALSE, TRUE),
                            palette = ifelse(isTRUE(compare_features), "Set1", "Spectral"), palcolor = NULL,
                            pt.size = NULL, pt.alpha = 1, bg_cutoff = 0, bg_color = "grey80",
-                           keep_scale = NULL, lower_quantile = 0, upper_quantile = 0.99, lower_cutoff = NULL, upper_cutoff = NULL,
+                           keep_scale = "feature", lower_quantile = 0, upper_quantile = 0.99, lower_cutoff = NULL, upper_cutoff = NULL,
                            add_density = FALSE, density_color = "grey80", density_filled = FALSE, density_filled_palette = "Greys", density_filled_palcolor = NULL,
                            cells.highlight = NULL, cols.highlight = "black", sizes.highlight = 1, alpha.highlight = 1, stroke.highlight = 0.5,
                            calculate_coexp = FALSE, compare_features = FALSE, color_blend_mode = c("blend", "average", "screen", "multiply"),
@@ -3343,6 +3343,7 @@ FeatureDimPlot3D <- function(srt, features, reduction = NULL, dims = c(1, 2, 3),
 #' @param pt.size A numeric value specifying the size of the data points. If NULL, the size is automatically determined. Default is NULL.
 #' @param pt.alpha A numeric value specifying the transparency of the data points. Default is 1.
 #' @param jitter.width A numeric value specifying the width of the jitter. Default is 0.5.
+#' @param jitter.height A numeric value specifying the height of the jitter. Default is 0.1.
 #' @param add_trend A logical indicating whether to add a trend line to the plot. Default is FALSE.
 #' @param trend_color A string specifying the color of the trend line. Default is "black".
 #' @param trend_linewidth A numeric value specifying the width of the trend line. Default is 1.
@@ -3466,7 +3467,7 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
                             palette = "Paired", palcolor = NULL, alpha = 1,
                             bg_palette = "Paired", bg_palcolor = NULL, bg_alpha = 0.2,
                             add_box = FALSE, box_color = "black", box_width = 0.1, box_ptsize = 2,
-                            add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5,
+                            add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5, jitter.height = 0.1,
                             add_trend = FALSE, trend_color = "black", trend_linewidth = 1, trend_ptsize = 2,
                             add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1,
                             cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
@@ -3519,7 +3520,7 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
           palette = palette, palcolor = palcolor, alpha = alpha,
           bg_palette = bg_palette, bg_palcolor = bg_palcolor, bg_alpha = bg_alpha,
           add_box = add_box, box_color = box_color, box_width = box_width, box_ptsize = box_ptsize,
-          add_point = add_point, pt.color = pt.color, pt.size = pt.size, pt.alpha = pt.alpha, jitter.width = jitter.width,
+          add_point = add_point, pt.color = pt.color, pt.size = pt.size, pt.alpha = pt.alpha, jitter.width = jitter.width, jitter.height = jitter.height,
           add_trend = add_trend, trend_color = trend_color, trend_linewidth = trend_linewidth, trend_ptsize = trend_ptsize,
           add_stat = add_stat, stat_color = stat_color, stat_size = stat_size,
           cells.highlight = cells.highlight, cols.highlight = cols.highlight, sizes.highlight = sizes.highlight, alpha.highlight = alpha.highlight,
@@ -3546,7 +3547,7 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
       palette = palette, palcolor = palcolor, alpha = alpha,
       bg_palette = bg_palette, bg_palcolor = bg_palcolor, bg_alpha = bg_alpha,
       add_box = add_box, box_color = box_color, box_width = box_width, box_ptsize = box_ptsize,
-      add_point = add_point, pt.color = pt.color, pt.size = pt.size, pt.alpha = pt.alpha, jitter.width = jitter.width,
+      add_point = add_point, pt.color = pt.color, pt.size = pt.size, pt.alpha = pt.alpha, jitter.width = jitter.width, jitter.height = jitter.height,
       add_trend = add_trend, trend_color = trend_color, trend_linewidth = trend_linewidth, trend_ptsize = trend_ptsize,
       add_stat = add_stat, stat_color = stat_color, stat_size = stat_size,
       cells.highlight = cells.highlight, cols.highlight = cols.highlight, sizes.highlight = sizes.highlight, alpha.highlight = alpha.highlight,
@@ -3662,7 +3663,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
                                palette = "Paired", palcolor = NULL, alpha = 1,
                                bg_palette = "Paired", bg_palcolor = NULL, bg_alpha = 0.2,
                                add_box = FALSE, box_color = "black", box_width = 0.1, box_ptsize = 2,
-                               add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5,
+                               add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5, jitter.height = 0.1,
                                add_trend = FALSE, trend_color = "black", trend_linewidth = 1, trend_ptsize = 2,
                                add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1,
                                cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
@@ -4162,7 +4163,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
         aes(x = .data[["group.by"]], y = .data[["value"]], linetype = rep(f, nrow(dat)), group = .data[["group.unique"]]),
         inherit.aes = FALSE,
         color = pt.color, size = pt.size, alpha = pt.alpha,
-        position = position_jitterdodge(jitter.width = jitter.width, dodge.width = 0.9, seed = 11), show.legend = FALSE
+        position = position_jitterdodge(jitter.width = jitter.width, jitter.height = jitter.height, dodge.width = 0.9, seed = 11), show.legend = FALSE
       ))
       if (!is.null(cells.highlight)) {
         cell_df <- subset(p$data, rownames(p$data) %in% cells.highlight)
@@ -4170,7 +4171,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
           p <- p + geom_point(
             data = cell_df, aes(x = .data[["group.by"]], y = .data[["value"]], linetype = rep(f, nrow(cell_df)), group = .data[["group.unique"]]), inherit.aes = FALSE,
             color = cols.highlight, size = sizes.highlight, alpha = alpha.highlight,
-            position = position_jitterdodge(jitter.width = jitter.width, dodge.width = 0.9, seed = 11), show.legend = FALSE
+            position = position_jitterdodge(jitter.width = jitter.width, jitter.height = jitter.height, dodge.width = 0.9, seed = 11), show.legend = FALSE
           )
         }
       }
@@ -7854,7 +7855,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
                          db = "GO_BP", TERM2GENE = NULL, TERM2NAME = NULL, minGSSize = 10, maxGSSize = 500,
                          GO_simplify = FALSE, GO_simplify_cutoff = "p.adjust < 0.05", simplify_method = "Wang", simplify_similarityCutoff = 0.7,
                          pvalueCutoff = NULL, padjustCutoff = 0.05, topTerm = 5, show_termid = FALSE, topWord = 20, words_excluded = NULL,
-                         nlabel = 0, features_label = NULL, label_size = 10, label_color = "black",
+                         nlabel = 20, features_label = NULL, label_size = 10, label_color = "black",
                          add_bg = FALSE, bg_alpha = 0.5,
                          add_dot = FALSE, dot_size = unit(8, "mm"),
                          add_reticle = FALSE, reticle_color = "grey",
diff --git a/R/SCP-workflow.R b/R/SCP-workflow.R
index ea368d83..66165414 100644
--- a/R/SCP-workflow.R
+++ b/R/SCP-workflow.R
@@ -116,6 +116,8 @@ check_srtList <- function(srtList, batch, assay = NULL,
       type <- "RNA"
     } else if (assay_type == "ChromatinAssay") {
       type <- "Chromatin"
+    } else {
+      type <- "Unknown"
     }
   }
 
diff --git a/R/utils.R b/R/utils.R
index 7d8b6c07..567b01f0 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -468,13 +468,13 @@ conda_python <- function(envname = NULL, conda = "auto", all = FALSE) {
     stop(sprintf(fmt, envname))
   }
   conda_envs <- reticulate::conda_list(conda = conda)
-  conda_envs <- conda_envs[grep(normalizePath(reticulate:::conda_info(conda = conda)$envs_dirs[1]), x = normalizePath(conda_envs$python), fixed = TRUE), , drop = FALSE]
+  conda_envs <- conda_envs[grep(normalizePath(reticulate:::conda_info(conda = conda)$envs_dirs[1], mustWork = FALSE), x = normalizePath(conda_envs$python, mustWork = FALSE), fixed = TRUE), , drop = FALSE]
   env <- conda_envs[conda_envs$name == envname, , drop = FALSE]
   if (nrow(env) == 0) {
     stop("conda environment \"", envname, "\" not found")
   }
   python <- if (all) env$python else env$python[[1L]]
-  return(normalizePath(as.character(python)))
+  return(normalizePath(as.character(python), mustWork = FALSE))
 }
 
 run_Python <- function(command, envir = .GlobalEnv) {
diff --git a/man/FeatureDimPlot.Rd b/man/FeatureDimPlot.Rd
index 048a7ab6..6620da4b 100644
--- a/man/FeatureDimPlot.Rd
+++ b/man/FeatureDimPlot.Rd
@@ -20,7 +20,7 @@ FeatureDimPlot(
   pt.alpha = 1,
   bg_cutoff = 0,
   bg_color = "grey80",
-  keep_scale = NULL,
+  keep_scale = "feature",
   lower_quantile = 0,
   upper_quantile = 0.99,
   lower_cutoff = NULL,
diff --git a/man/FeatureStatPlot.Rd b/man/FeatureStatPlot.Rd
index 66989ceb..fbb0a04d 100644
--- a/man/FeatureStatPlot.Rd
+++ b/man/FeatureStatPlot.Rd
@@ -33,6 +33,7 @@ FeatureStatPlot(
   pt.size = NULL,
   pt.alpha = 1,
   jitter.width = 0.5,
+  jitter.height = 0.1,
   add_trend = FALSE,
   trend_color = "black",
   trend_linewidth = 1,
@@ -134,6 +135,8 @@ FeatureStatPlot(
 
 \item{jitter.width}{A numeric value specifying the width of the jitter. Default is 0.5.}
 
+\item{jitter.height}{A numeric value specifying the height of the jitter. Default is 0.1.}
+
 \item{add_trend}{A logical indicating whether to add a trend line to the plot. Default is FALSE.}
 
 \item{trend_color}{A string specifying the color of the trend line. Default is "black".}
diff --git a/man/GroupHeatmap.Rd b/man/GroupHeatmap.Rd
index 17ec0d2c..d454313f 100644
--- a/man/GroupHeatmap.Rd
+++ b/man/GroupHeatmap.Rd
@@ -80,7 +80,7 @@ GroupHeatmap(
   show_termid = FALSE,
   topWord = 20,
   words_excluded = NULL,
-  nlabel = 0,
+  nlabel = 20,
   features_label = NULL,
   label_size = 10,
   label_color = "black",
diff --git a/man/RunSCExplorer.Rd b/man/RunSCExplorer.Rd
index ca2401ea..03ca1990 100644
--- a/man/RunSCExplorer.Rd
+++ b/man/RunSCExplorer.Rd
@@ -22,6 +22,7 @@ RunSCExplorer(
   initial_size = 4,
   initial_ncol = 3,
   initial_arrange = "Row",
+  initial_raster = "No",
   session_workers = 2,
   plotting_workers = 8,
   create_script = TRUE,

From ea08bbb2e0bdbc14ebb5a20200cd2c31f1054a2a Mon Sep 17 00:00:00 2001
From: zhanghao-njmu <542370159@qq.com>
Date: Thu, 9 Nov 2023 03:33:06 +0800
Subject: [PATCH 2/4] Fix the "keep_scale" bug in FeatureDimPlot

---
 R/SCP-plot.R | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/SCP-plot.R b/R/SCP-plot.R
index ce1d9c5e..def37837 100644
--- a/R/SCP-plot.R
+++ b/R/SCP-plot.R
@@ -2121,6 +2121,8 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
   if (!is.numeric(dat_exp) && !inherits(dat_exp, "Matrix")) {
     stop("'features' must be type of numeric variable.")
   }
+  dat_exp[, features][dat_exp[, features] <= bg_cutoff] <- NA
+
   if (length(features) > 50 && !isTRUE(force)) {
     warning("More than 50 features to be plotted", immediate. = TRUE)
     answer <- askYesNo("Are you sure to continue?", default = FALSE)
@@ -2195,7 +2197,6 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
     plist <- lapply(levels(dat_sp[[split.by]]), function(s) {
       dat <- dat_split[[ifelse(split.by == "All.groups", 1, s)]][, , drop = FALSE]
       for (f in features) {
-        dat[, f][dat[, f] <= bg_cutoff] <- NA
         if (any(is.infinite(dat[, f]))) {
           dat[, f][which(dat[, f] == max(dat[, f], na.rm = TRUE))] <- max(dat[, f][is.finite(dat[, f])], na.rm = TRUE)
           dat[, f][which(dat[, f] == min(dat[, f], na.rm = TRUE))] <- min(dat[, f][is.finite(dat[, f])], na.rm = TRUE)
@@ -2502,7 +2503,6 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
       f <- comb[i, "feature"]
       s <- comb[i, "split"]
       dat <- dat_split[[ifelse(split.by == "All.groups", 1, s)]][, c(colnames(dat_use), f), drop = FALSE]
-      dat[, f][dat[, f] <= bg_cutoff] <- NA
       if (any(is.infinite(dat[, f]))) {
         dat[, f][dat[, f] == max(dat[, f], na.rm = TRUE)] <- max(dat[, f][is.finite(dat[, f])], na.rm = TRUE)
         dat[, f][dat[, f] == min(dat[, f], na.rm = TRUE)] <- min(dat[, f][is.finite(dat[, f])], na.rm = TRUE)

From 36969ca24dd71ded4cf496a5226f1f6e70065114 Mon Sep 17 00:00:00 2001
From: zhanghao-njmu <542370159@qq.com>
Date: Tue, 14 Nov 2023 15:13:01 +0800
Subject: [PATCH 3/4] Fix some bugs

---
 DESCRIPTION             |   4 +-
 NAMESPACE               |   6 +
 R/SCP-analysis.R        | 396 +++++++++++++++++++++++++++++++++++++---
 R/SCP-app.R             | 122 +++++++------
 R/SCP-cell_annotation.R |  16 +-
 R/SCP-cellqc.R          |   2 +-
 R/SCP-plot.R            | 156 ++++++++--------
 R/SCP-workflow.R        |   8 +-
 R/Seurat-function.R     |  40 ++--
 R/utils.R               |  31 ++--
 man/CellCorHeatmap.Rd   |  10 +-
 man/CellScoring.Rd      |   2 +-
 man/DynamicHeatmap.Rd   |  14 +-
 man/FeatureHeatmap.Rd   |   6 +-
 man/FeatureStatPlot.Rd  |   5 +-
 man/FetchH5.Rd          |   8 +-
 man/GeneConvert.Rd      |   2 +-
 man/GroupHeatmap.Rd     |  29 ++-
 man/RunSCExplorer.Rd    |  12 +-
 man/as_matrix.Rd        |  11 +-
 src/RcppExports.cpp     |   2 +-
 src/asMatrix.cpp        |  23 ++-
 22 files changed, 647 insertions(+), 258 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 80d75306..55efbad8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -21,6 +21,8 @@ Imports:
     ComplexHeatmap (>= 2.13.0),
     data.table,
     dplyr (>= 1.1.0),
+    future,
+    future.apply,
     ggnewscale,
     ggplot2 (>= 3.4.0),
     ggrepel,
@@ -37,6 +39,7 @@ Imports:
     mgcv,
     Matrix,
     patchwork,
+    pbapply,
     png,
     plotly,
     proxyC,
@@ -68,7 +71,6 @@ Suggests:
     devtools,
     DDRTree,
     e1071,
-    future,
     ggpubr,
     ggridges,
     ggsignif,
diff --git a/NAMESPACE b/NAMESPACE
index 477dfd27..066312d5 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -57,6 +57,7 @@ export(FeatureDimPlot3D)
 export(FeatureHeatmap)
 export(FeatureStatPlot)
 export(FetchH5)
+export(FindExpressedMarkers)
 export(GSEAPlot)
 export(GeneConvert)
 export(GraphPlot)
@@ -206,6 +207,7 @@ importFrom(ComplexHeatmap,width.Legends)
 importFrom(HDF5Array,TENxMatrix)
 importFrom(HDF5Array,writeTENxMatrix)
 importFrom(Matrix,Matrix)
+importFrom(Matrix,as.matrix)
 importFrom(Matrix,colMeans)
 importFrom(Matrix,colSums)
 importFrom(Matrix,rowMeans)
@@ -228,6 +230,7 @@ importFrom(Seurat,Assays)
 importFrom(Seurat,AverageExpression)
 importFrom(Seurat,CaseMatch)
 importFrom(Seurat,Cells)
+importFrom(Seurat,Command)
 importFrom(Seurat,CreateAssayObject)
 importFrom(Seurat,CreateDimReducObject)
 importFrom(Seurat,CreateSeuratObject)
@@ -327,6 +330,8 @@ importFrom(dplyr,reframe)
 importFrom(dplyr,slice_head)
 importFrom(dplyr,summarise)
 importFrom(dplyr,summarise_at)
+importFrom(future,nbrOfWorkers)
+importFrom(future.apply,future_sapply)
 importFrom(ggforce,geom_mark_ellipse)
 importFrom(ggforce,geom_mark_hull)
 importFrom(ggnewscale,new_scale)
@@ -511,6 +516,7 @@ importFrom(methods,new)
 importFrom(methods,slot)
 importFrom(methods,slotNames)
 importFrom(patchwork,wrap_plots)
+importFrom(pbapply,pbsapply)
 importFrom(plotly,add_trace)
 importFrom(plotly,as_widget)
 importFrom(plotly,layout)
diff --git a/R/SCP-analysis.R b/R/SCP-analysis.R
index 28373c27..a8b3df7e 100644
--- a/R/SCP-analysis.R
+++ b/R/SCP-analysis.R
@@ -60,7 +60,7 @@
 #'   by = list(res$geneID_expand[, "symbol"]), FUN = sum
 #' )
 #' rownames(homologs_counts) <- homologs_counts[, 1]
-#' homologs_counts <- as(as.matrix(homologs_counts[, -1]), "dgCMatrix")
+#' homologs_counts <- as(as_matrix(homologs_counts[, -1]), "dgCMatrix")
 #' homologs_counts
 #'
 #' @importFrom R.cache loadCache saveCache
@@ -470,8 +470,8 @@ searchDatasets <- function(datasets, pattern) {
 #' @importFrom R.cache loadCache saveCache
 #' @export
 CC_GenePrefetch <- function(species = "Homo_sapiens", Ensembl_version = 103, mirror = NULL, max_tries = 5, use_cached_gene = TRUE) {
-  cc_S_genes <- Seurat::cc.genes.updated.2019$s.genes
-  cc_G2M_genes <- Seurat::cc.genes.updated.2019$g2m.genes
+  S <- Seurat::cc.genes.updated.2019$s.genes
+  G2M <- Seurat::cc.genes.updated.2019$g2m.genes
   res <- NULL
   if (species != "Homo_sapiens") {
     if (isTRUE(use_cached_gene)) {
@@ -479,7 +479,7 @@ CC_GenePrefetch <- function(species = "Homo_sapiens", Ensembl_version = 103, mir
     }
     if (is.null(res)) {
       res <- GeneConvert(
-        geneID = unique(c(cc_S_genes, cc_G2M_genes)),
+        geneID = unique(c(S, G2M)),
         geneID_from_IDtype = "symbol",
         geneID_to_IDtype = "symbol",
         species_from = "Homo_sapiens",
@@ -493,13 +493,13 @@ CC_GenePrefetch <- function(species = "Homo_sapiens", Ensembl_version = 103, mir
       message("Using cached conversion results for ", species)
     }
     genes <- res[["geneID_collapse"]]
-    cc_S_genes <- unlist(genes[cc_S_genes[cc_S_genes %in% rownames(genes)], "symbol"])
-    cc_G2M_genes <- unlist(genes[cc_G2M_genes[cc_G2M_genes %in% rownames(genes)], "symbol"])
+    S <- unlist(genes[S[S %in% rownames(genes)], "symbol"])
+    G2M <- unlist(genes[G2M[G2M %in% rownames(genes)], "symbol"])
   }
   return(list(
     res = res,
-    cc_S_genes = cc_S_genes,
-    cc_G2M_genes = cc_G2M_genes
+    S = S,
+    G2M = G2M
   ))
 }
 
@@ -621,14 +621,14 @@ AddModuleScore2 <- function(object, slot = "data", features, pool = NULL, nbin =
   #   return(list(features.use, ctrl.use))
   # }, BPPARAM = BPPARAM)
   # features.scores <- bpaggregate(
-  #   x = as.matrix(assay.data[unlist(lapply(features_collapse, function(x) x[[1]])), ]),
+  #   x = as_matrix(assay.data[unlist(lapply(features_collapse, function(x) x[[1]])), ]),
   #   by = list(unlist(lapply(1:length(features_collapse), function(x) rep(x, length(features_collapse[[x]][[1]]))))),
   #   FUN = mean,
   #   BPPARAM = BPPARAM
   # )
   # features.scores <- features.scores[,-1]
   # ctrl.scores <- bpaggregate(
-  #   x = as.matrix(assay.data[unlist(lapply(features_collapse, function(x) x[[2]])), ]),
+  #   x = as_matrix(assay.data[unlist(lapply(features_collapse, function(x) x[[2]])), ]),
   #   by = list(unlist(lapply(1:length(features_collapse), function(x) rep(x, length(features_collapse[[x]][[2]]))))),
   #   FUN = mean,
   #   BPPARAM = BPPARAM
@@ -672,7 +672,7 @@ AddModuleScore2 <- function(object, slot = "data", features, pool = NULL, nbin =
 #' ccgenes <- CC_GenePrefetch("Mus_musculus")
 #' pancreas_sub <- CellScoring(
 #'   srt = pancreas_sub,
-#'   features = list(S = ccgenes$cc_S_genes, G2M = ccgenes$cc_G2M_genes),
+#'   features = list(S = ccgenes$S, G2M = ccgenes$G2M),
 #'   method = "Seurat", name = "CC"
 #' )
 #' CellDimPlot(pancreas_sub, "CC_classification")
@@ -862,7 +862,7 @@ CellScoring <- function(srt, features = NULL, slot = "data", assay = NULL, split
       colnames(scores) <- make.names(paste(name, names(features_nm), sep = "_"))
     } else if (method == "AUCell") {
       check_R("AUCell")
-      CellRank <- AUCell::AUCell_buildRankings(as.matrix(GetAssayData(srt_sp, slot = slot, assay = assay)), BPPARAM = BPPARAM, plotStats = FALSE)
+      CellRank <- AUCell::AUCell_buildRankings(as_matrix(GetAssayData(srt_sp, slot = slot, assay = assay)), BPPARAM = BPPARAM, plotStats = FALSE)
       cells_AUC <- AUCell::AUCell_calcAUC(
         geneSets = features,
         rankings = CellRank,
@@ -885,7 +885,7 @@ CellScoring <- function(srt, features = NULL, slot = "data", assay = NULL, split
   scores_mat <- do.call(rbind, lapply(scores_list, function(x) x[intersect(rownames(x), colnames(srt)), features_used, drop = FALSE]))
 
   if (isTRUE(new_assay)) {
-    srt[[name]] <- CreateAssayObject(counts = t(as.matrix(scores_mat[colnames(srt), , drop = FALSE])))
+    srt[[name]] <- CreateAssayObject(counts = t(as_matrix(scores_mat[colnames(srt), , drop = FALSE])))
     srt[[name]] <- AddMetaData(object = srt[[name]], metadata = data.frame(termnames = features_nm_used[colnames(scores_mat)]))
   } else {
     srt <- AddMetaData(object = srt, metadata = scores_mat)
@@ -1077,7 +1077,7 @@ FindConservedMarkers2 <- function(object, grouping.var, ident.1, ident.2 = NULL,
   object.var <- FetchData(object = object, vars = grouping.var)
   levels.split <- names(x = sort(x = table(object.var[, 1])))
   num.groups <- length(levels.split)
-  assay <- assay %||% DefaultAssay(srt)
+  assay <- assay %||% DefaultAssay(object)
 
   cells <- list()
   for (i in 1:num.groups) {
@@ -1217,6 +1217,353 @@ FindConservedMarkers2 <- function(object, grouping.var, ident.1, ident.2 = NULL,
   return(markers.combined)
 }
 
+#' @examples
+#' markers <- FindExpressedMarkers(pancreas_sub, cells.1 = WhichCells(pancreas_sub, expression = Phase == "G2M"))
+#' head(markers)
+#' FeatureStatPlot(pancreas_sub, rownames(markers)[1], group.by = "Phase", add_point = TRUE)
+#' @importFrom Matrix rowSums
+#' @importFrom SeuratObject PackageCheck FetchData WhichCells SetIdent Idents
+#' @importFrom Seurat FindMarkers FoldChange Command
+#' @importFrom pbapply pbsapply
+#' @export
+FindExpressedMarkers <- function(object, ident.1 = NULL, ident.2 = NULL, cells.1 = NULL, cells.2 = NULL,
+                                 features = NULL, assay = NULL, slot = "data", min.expression = 0,
+                                 test.use = "wilcox", logfc.threshold = 0.25, base = 2, pseudocount.use = 1, mean.fxn = NULL, fc.name = NULL,
+                                 min.pct = 0.1, min.diff.pct = -Inf, max.cells.per.ident = Inf, latent.vars = NULL, only.pos = FALSE,
+                                 min.cells.group = 3, min.cells.feature = 3,
+                                 norm.method = "LogNormalize", verbose = TRUE, ...) {
+  ########## FindMarkers.Seurat ##########
+
+  assay <- assay %||% DefaultAssay(object)
+  data.use <- object[[assay]]
+
+  if (!is.null(cells.1)) {
+    if (is.null(cells.2)) {
+      cells.2 <- setdiff(colnames(object), cells.1)
+    }
+  } else {
+    cells.1 <- WhichCells(object = object, idents = ident.1)
+    cells.2 <- WhichCells(object = object, idents = ident.2)
+  }
+
+  # fetch latent.vars
+  if (!is.null(x = latent.vars)) {
+    latent.vars <- FetchData(
+      object = object,
+      vars = latent.vars,
+      cells = c(cells.1, cells.2)
+    )
+  }
+
+  ########## FindMarkers.Assay ##########
+
+  object <- data.use
+
+  pseudocount.use <- pseudocount.use %||% 1
+  data.slot <- ifelse(
+    test = test.use %in% c("negbinom", "poisson", "DESeq2"),
+    yes = "counts",
+    no = slot
+  )
+  data.use <- GetAssayData(object = object, slot = data.slot)
+  data.use <- data.use[rowSums(data.use) > 0, ]
+  data.use <- as_matrix(data.use)
+  data.use[data.use <= min.expression] <- NA
+  counts <- switch(
+    EXPR = data.slot,
+    "scale.data" = GetAssayData(object = object, slot = "counts"),
+    numeric()
+  )
+
+  ########## FoldChange.Assay ##########
+  features <- features %||% rownames(x = data.use)
+  slot <- data.slot
+
+  # By default run as if LogNormalize is done
+  log1pdata.mean.fxn <- function(x) {
+    return(log(x = rowMeans(x = expm1(x), na.rm = TRUE) + pseudocount.use, base = base))
+  }
+  scaledata.mean.fxn <- function(x) {
+    return(rowMeans(x, na.rm = TRUE))
+  }
+  counts.mean.fxn <- function(x) {
+    return(log(x = rowMeans(x = x, na.rm = TRUE) + pseudocount.use, base = base))
+  }
+  if (!is.null(x = norm.method)) {
+    # For anything apart from log normalization set to rowMeans
+    if (norm.method != "LogNormalize") {
+      new.mean.fxn <- counts.mean.fxn
+    } else {
+      new.mean.fxn <- switch(
+        EXPR = slot,
+        "data" = log1pdata.mean.fxn,
+        "scale.data" = scaledata.mean.fxn,
+        "counts" = counts.mean.fxn,
+        counts.mean.fxn
+      )
+    }
+  } else {
+    # If no normalization method is passed use slots to decide mean function
+    new.mean.fxn <- switch(
+      EXPR = slot,
+      "data" = log1pdata.mean.fxn,
+      "scale.data" = scaledata.mean.fxn,
+      "counts" = counts.mean.fxn,
+      log1pdata.mean.fxn
+    )
+  }
+  mean.fxn <- mean.fxn %||% new.mean.fxn
+  # Omit the decimal value of e from the column name if base == exp(1)
+  base.text <- ifelse(
+    test = base == exp(1),
+    yes = "",
+    no = base
+  )
+  fc.name <- fc.name %||% ifelse(
+    test = slot == "scale.data",
+    yes = "avg_diff",
+    no = paste0("avg_log", base.text, "FC")
+  )
+  fc.results <- FoldChange.default(
+    object = data.use,
+    cells.1 = cells.1,
+    cells.2 = cells.2,
+    features = features,
+    mean.fxn = mean.fxn,
+    fc.name = fc.name
+  )
+
+  ########## FindMarkers.default ##########
+
+  object <- data.use
+  slot <- data.slot
+
+  Seurat:::ValidateCellGroups(
+    object = object,
+    cells.1 = cells.1,
+    cells.2 = cells.2,
+    min.cells.group = min.cells.group
+  )
+
+  # reset parameters so no feature filtering is performed
+  if (test.use %in% "DESeq2") {
+    features <- rownames(x = object)
+    min.diff.pct <- -Inf
+    logfc.threshold <- 0
+  }
+  data <- switch(
+    EXPR = slot,
+    "scale.data" = counts,
+    object
+  )
+  # feature selection (based on percentages)
+  alpha.min <- pmax(fc.results$pct.1, fc.results$pct.2)
+  names(x = alpha.min) <- rownames(x = fc.results)
+  features <- names(x = which(x = alpha.min >= min.pct))
+  if (length(x = features) == 0) {
+    warning("No features pass min.pct threshold; returning empty data.frame")
+    return(fc.results[features, ])
+  }
+  alpha.diff <- alpha.min - pmin(fc.results$pct.1, fc.results$pct.2)
+  features <- names(
+    x = which(x = alpha.min >= min.pct & alpha.diff >= min.diff.pct)
+  )
+  if (length(x = features) == 0) {
+    warning("No features pass min.diff.pct threshold; returning empty data.frame")
+    return(fc.results[features, ])
+  }
+  # feature selection (based on logFC)
+  if (slot != "scale.data") {
+    total.diff <- fc.results[, 1] # first column is logFC
+    names(total.diff) <- rownames(fc.results)
+    features.diff <- if (only.pos) {
+      names(x = which(x = total.diff >= logfc.threshold))
+    } else {
+      names(x = which(x = abs(x = total.diff) >= logfc.threshold))
+    }
+    features <- intersect(x = features, y = features.diff)
+    if (length(x = features) == 0) {
+      warning("No features pass logfc.threshold threshold; returning empty data.frame")
+      return(fc.results[features, ])
+    }
+  }
+  # subsample cell groups if they are too large
+  if (max.cells.per.ident < Inf) {
+    set.seed(seed = random.seed)
+    if (length(x = cells.1) > max.cells.per.ident) {
+      cells.1 <- sample(x = cells.1, size = max.cells.per.ident)
+    }
+    if (length(x = cells.2) > max.cells.per.ident) {
+      cells.2 <- sample(x = cells.2, size = max.cells.per.ident)
+    }
+    if (!is.null(x = latent.vars)) {
+      latent.vars <- latent.vars[c(cells.1, cells.2), , drop = FALSE]
+    }
+  }
+
+  de.results <- PerformDE(
+    object = object,
+    cells.1 = cells.1,
+    cells.2 = cells.2,
+    features = features,
+    test.use = test.use,
+    verbose = verbose,
+    min.cells.feature = min.cells.feature,
+    latent.vars = latent.vars,
+    ...
+  )
+  de.results <- cbind(de.results, fc.results[rownames(x = de.results), , drop = FALSE])
+  if (only.pos) {
+    de.results <- de.results[de.results[, 2] > 0, , drop = FALSE]
+  }
+  if (test.use %in% "roc") {
+    de.results <- de.results[order(-de.results$power, -de.results[, 1]), ]
+  } else {
+    de.results <- de.results[order(de.results$p_val, -de.results[, 1]), ]
+    de.results$p_val_adj <- p.adjust(
+      p = de.results$p_val,
+      method = "bonferroni",
+      n = nrow(x = object)
+    )
+  }
+
+  return(de.results)
+}
+
+FoldChange.default <- function(object, cells.1, cells.2, mean.fxn, fc.name, features = NULL, ...) {
+  features <- features %||% rownames(x = object)
+  # Calculate percent expressed
+  thresh.min <- 0
+  pct.1 <- round(
+    x = rowSums(x = object[features, cells.1, drop = FALSE] > thresh.min, na.rm = TRUE) /
+      length(x = cells.1),
+    digits = 3
+  )
+  pct.2 <- round(
+    x = rowSums(x = object[features, cells.2, drop = FALSE] > thresh.min, na.rm = TRUE) /
+      length(x = cells.2),
+    digits = 3
+  )
+  # Calculate fold change
+  data.1 <- mean.fxn(object[features, cells.1, drop = FALSE])
+  data.2 <- mean.fxn(object[features, cells.2, drop = FALSE])
+  fc <- (data.1 - data.2)
+  fc.results <- as.data.frame(x = cbind(fc, pct.1, pct.2))
+  colnames(fc.results) <- c(fc.name, "pct.1", "pct.2")
+  return(fc.results)
+}
+
+
+PerformDE <- function(object, cells.1, cells.2, features, test.use, verbose, min.cells.feature, latent.vars, ...) {
+  if (!(test.use %in% c("negbinom", "poisson", "MAST", "LR")) && !is.null(x = latent.vars)) {
+    warning(
+      "'latent.vars' is only used for the following tests: ",
+      paste(c("negbinom", "poisson", "MAST", "LR"), collapse = ", "),
+      call. = FALSE,
+      immediate. = TRUE
+    )
+  }
+  data.use <- object[features, c(cells.1, cells.2), drop = FALSE]
+  data.use <- as_matrix(data.use)
+
+  de.results <- switch(
+    EXPR = test.use,
+    "wilcox" = WilcoxDETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      verbose = verbose,
+      ...
+    ),
+    "bimod" = Seurat:::DiffExpTest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      verbose = verbose
+    ),
+    "roc" = Seurat:::MarkerTest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      verbose = verbose
+    ),
+    "t" = Seurat:::DiffTTest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      verbose = verbose
+    ),
+    "negbinom" = Seurat:::GLMDETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      min.cells = min.cells.feature,
+      latent.vars = latent.vars,
+      test.use = test.use,
+      verbose = verbose
+    ),
+    "poisson" = Seurat:::GLMDETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      min.cells = min.cells.feature,
+      latent.vars = latent.vars,
+      test.use = test.use,
+      verbose = verbose
+    ),
+    "MAST" = Seurat:::MASTDETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      latent.vars = latent.vars,
+      verbose = verbose,
+      ...
+    ),
+    "DESeq2" = Seurat:::DESeq2DETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      verbose = verbose,
+      ...
+    ),
+    "LR" = Seurat:::LRDETest(
+      data.use = data.use,
+      cells.1 = cells.1,
+      cells.2 = cells.2,
+      latent.vars = latent.vars,
+      verbose = verbose
+    ),
+    stop("Unknown test: ", test.use)
+  )
+  return(de.results)
+}
+
+#' @importFrom future nbrOfWorkers
+#' @importFrom future.apply future_sapply
+#' @importFrom pbapply pbsapply
+WilcoxDETest <- function(data.use, cells.1, cells.2, verbose = TRUE, ...) {
+  data.use <- data.use[, c(cells.1, cells.2), drop = FALSE]
+  j <- seq_len(length.out = length(x = cells.1))
+  my.sapply <- ifelse(
+    test = verbose && nbrOfWorkers() == 1,
+    yes = pbsapply,
+    no = future_sapply
+  )
+  check_R("limma")
+  p_val <- my.sapply(
+    X = 1:nrow(x = data.use),
+    FUN = function(x) {
+      keep <- colnames(data.use)[!is.na(data.use[x, ])]
+      j <- seq_len(length.out = length(x = intersect(cells.1, keep)))
+      statistics <- data.use[x, keep]
+      return(min(2 * min(limma::rankSumTestWithCorrelation(index = j, statistics = statistics)), 1))
+    }
+  )
+
+  return(data.frame(p_val, row.names = rownames(x = data.use)))
+}
+
+
 #' Differential gene test
 #'
 #' This function utilizes the Seurat package to perform a differential expression (DE) test on gene expression data.
@@ -1689,6 +2036,7 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
         srt@tools[[paste0("DEtest_", group_by)]][[paste0("ConservedMarkers_", test.use)]] <- data.frame()
       }
     }
+
     if (markers_type == "disturbed") {
       sub_BPPARAM <- SerialParam()
       bpprogressbar(sub_BPPARAM) <- FALSE
@@ -4166,8 +4514,8 @@ orderCells <- function(cds, root_state = NULL, num_paths = NULL, reverse = NULL)
       num_paths <- 1
     }
     adjusted_S <- t(cds@reducedDimS)
-    dp <- as.matrix(stats::dist(adjusted_S))
-    cellPairwiseDistances(cds) <- as.matrix(stats::dist(adjusted_S))
+    dp <- as_matrix(stats::dist(adjusted_S))
+    cellPairwiseDistances(cds) <- as_matrix(stats::dist(adjusted_S))
     gp <- igraph::graph.adjacency(dp, mode = "undirected", weighted = TRUE)
     dp_mst <- igraph::minimum.spanning.tree(gp)
     monocle::minSpanningTree(cds) <- dp_mst
@@ -4239,7 +4587,7 @@ project2MST <- function(cds, Projection_Method) {
   cds <- monocle:::findNearestPointOnMST(cds)
   closest_vertex <- cds@auxOrderingData[["DDRTree"]]$pr_graph_cell_proj_closest_vertex
   closest_vertex_names <- colnames(Y)[closest_vertex]
-  closest_vertex_df <- as.matrix(closest_vertex)
+  closest_vertex_df <- as_matrix(closest_vertex)
   row.names(closest_vertex_df) <- row.names(closest_vertex)
   tip_leaves <- names(which(igraph::degree(dp_mst) == 1))
   if (!is.function(Projection_Method)) {
@@ -4261,13 +4609,13 @@ project2MST <- function(cds, Projection_Method) {
         distance <- c(distance, stats::dist(rbind(Z_i, tmp)))
       }
       if (!inherits(projection, "matrix")) {
-        projection <- as.matrix(projection)
+        projection <- as_matrix(projection)
       }
       P[, i] <- projection[which(distance == min(distance))[1], ]
     }
   }
   colnames(P) <- colnames(Z)
-  dp <- as.matrix(stats::dist(t(P)))
+  dp <- as_matrix(stats::dist(t(P)))
   min_dist <- min(dp[dp != 0])
   dp <- dp + min_dist
   diag(dp) <- 0
@@ -4707,9 +5055,9 @@ RunDynamicFeatures <- function(srt, lineages, features = NULL, suffix = lineages
     t <- srt_sub[[l, drop = TRUE]]
     t <- t[is.finite(t)]
     t_ordered <- t[order(t)]
-    Y_ordered <- as.matrix(Y[features, names(t_ordered), drop = FALSE])
+    Y_ordered <- as_matrix(Y[features, names(t_ordered), drop = FALSE])
     l_libsize <- Y_libsize[names(t_ordered)]
-    raw_matrix <- as.matrix(cbind(data.frame(pseudotime = t_ordered), t(Y_ordered)))
+    raw_matrix <- as_matrix(cbind(data.frame(pseudotime = t_ordered), t(Y_ordered)))
 
     # df <- data.frame(x = rowMeans(Y_ordered), y = MatrixGenerics::rowVars(Y_ordered))
     # p <- ggplot(df, aes(x = .data[["x"]], y = .data[["y"]])) +
@@ -5228,7 +5576,7 @@ adata_to_srt <- function(adata) {
         next
       }
       if (!inherits(obsm, "matrix")) {
-        obsm <- as.matrix(obsm)
+        obsm <- as_matrix(obsm)
       }
       k <- gsub(pattern = "^X_", replacement = "", x = py_to_r_auto(k))
       colnames(obsm) <- paste0(k, "_", seq_len(ncol(obsm)))
@@ -5277,7 +5625,7 @@ adata_to_srt <- function(adata) {
         next
       }
       if (!inherits(varm, "matrix")) {
-        varm <- as.matrix(varm)
+        varm <- as_matrix(varm)
       }
       colnames(varm) <- paste0(py_to_r_auto(k), "_", seq_len(ncol(varm)))
       rownames(varm) <- py_to_r_auto(adata$var_names$values)
@@ -5298,7 +5646,7 @@ adata_to_srt <- function(adata) {
         next
       }
       if (!inherits(varp, "matrix")) {
-        varp <- as.matrix(varp)
+        varp <- as_matrix(varp)
       }
       colnames(varp) <- py_to_r_auto(adata$var_names$values)
       rownames(varp) <- py_to_r_auto(adata$var_names$values)
diff --git a/R/SCP-app.R b/R/SCP-app.R
index b30c405f..d2003679 100644
--- a/R/SCP-app.R
+++ b/R/SCP-app.R
@@ -323,7 +323,13 @@ PrepareSCExplorer <- function(object,
 #' data("pancreas_sub")
 #' pancreas_sub <- Standard_SCP(pancreas_sub)
 #' PrepareSCExplorer(pancreas_sub, base_dir = "./SCExplorer")
-#' srt <- FetchH5(DataFile = "./SCExplorer/Data.hdf5", MetaFile = "./SCExplorer/Meta.hdf5", features = c("Ins1", "Ghrl"), metanames = c("SubCellType", "Phase"), reduction = "UMAP")
+#' srt <- FetchH5(
+#'   DataFile = "./SCExplorer/Data.hdf5",
+#'   MetaFile = "./SCExplorer/Meta.hdf5",
+#'   features = c("Ins1", "Ghrl"),
+#'   metanames = c("SubCellType", "Phase"),
+#'   reduction = "UMAP"
+#' )
 #' CellDimPlot(srt, group.by = c("SubCellType", "Phase"), reduction = "UMAP")
 #' FeatureDimPlot(srt, features = c("Ins1", "Ghrl"), reduction = "UMAP")
 #' }
@@ -506,13 +512,14 @@ CreateSeuratObject2 <- function(counts, project = "SeuratProject", assay = "RNA"
 #' @param initial_feature A string. The initial feature to be loaded into the app. Default is NULL.
 #' @param initial_assay A string. The initial assay to be loaded into the app. Default is NULL.
 #' @param initial_slot A string. The initial slot to be loaded into the app. Default is NULL.
-#' @param initial_label A string. Whether to add labels in the initial plot. Default is "No".
+#' @param initial_label A string. Whether to add labels in the initial plot. Default is FALSE.
 #' @param initial_cell_palette A string. The initial color palette for cells. Default is "Paired".
 #' @param initial_feature_palette A string. The initial color palette for features. Default is "Spectral".
 #' @param initial_theme A string. The initial theme for plots. Default is "theme_scp".
 #' @param initial_size A numeric. The initial size of plots. Default is 4.
 #' @param initial_ncol A numeric. The initial number of columns for arranging plots. Default is 3.
-#' @param initial_arrange A string. The initial arrangement of plots. Default is "Row".
+#' @param initial_arrange A logical. Whether to use "Row" as the initial arrangement. Default is TRUE.
+#' @param initial_raster A logical. Whether to perform rasterization in the initial plot. By default, it is set to automatic, meaning it will be TRUE if the number of cells in the initial datasets exceeds 100,000.
 #' @param session_workers A numeric. The number of workers for concurrent execution in an asynchronous programming session. Default is 2.
 #' @param plotting_workers A numeric. The number of threads per worker for parallel plotting. Default is 8.
 #' @param create_script A logical. Whether to create the SCExplorer app script. Default is TRUE.
@@ -577,14 +584,14 @@ RunSCExplorer <- function(base_dir = "SCExplorer",
                           initial_feature = NULL,
                           initial_assay = NULL,
                           initial_slot = NULL,
-                          initial_label = "No",
+                          initial_label = FALSE,
                           initial_cell_palette = "Paired",
                           initial_feature_palette = "Spectral",
                           initial_theme = "theme_scp",
                           initial_size = 4,
                           initial_ncol = 3,
-                          initial_arrange = "Row",
-                          initial_raster = "No",
+                          initial_arrange = NULL,
+                          initial_raster = NULL,
                           session_workers = 2,
                           plotting_workers = 8,
                           create_script = TRUE,
@@ -634,6 +641,7 @@ if (!initial_assay %in% assays) {
 if (!initial_slot %in% slots) {
   stop("initial_slot is not in the dataset ", initial_slot, " in the DataFile")
 }
+all_cells <- rhdf5::h5read(DataFile, name = paste0("/", initial_dataset, "/cells"))
 
 data <- HDF5Array::TENxMatrix(filepath = DataFile, group = paste0("/", initial_dataset, "/", initial_assay, "/", initial_slot))
 all_features <- colnames(data)
@@ -653,6 +661,12 @@ if (is.null(initial_group)) {
 if (is.null(initial_feature)) {
   initial_feature <- meta_features_name[1]
 }
+if (is.null(initial_arrange)) {
+  initial_arrange <- TRUE
+}
+if (is.null(initial_raster)) {
+  initial_raster <- length(all_cells) > 1e5
+}
 
 palette_list <- SCP::palette_list
 theme_list <- list(
@@ -714,7 +728,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "label1",
                 label = "Label",
-                choices = c("Yes", "No"),
+                choices = c("Yes" = TRUE, "No" = FALSE),
                 selected = initial_label,
                 inline = TRUE
               )
@@ -724,7 +738,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "raster1",
                 label = "Raster",
-                choices = c("Yes", "No"),
+                choices = c("Yes" = TRUE, "No" = FALSE),
                 selected = initial_raster,
                 inline = TRUE
               )
@@ -737,7 +751,7 @@ ui <- fluidPage(
                 inputId = "pt_size1",
                 label = "Point size",
                 value = 1,
-                min = 0.5,
+                min = 0.1,
                 max = 10,
                 step = 0.5,
                 width = "150px"
@@ -774,7 +788,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "arrange1",
                 label = "Arrange by",
-                choices = c("Row", "Column"),
+                choices = c("Row" = TRUE, "Column" = FALSE),
                 selected = initial_arrange
               )
             )
@@ -895,8 +909,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "coExp2",
                 label = "Co-expression",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               ),
             ),
@@ -915,7 +929,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "raster2",
                 label = "Raster",
-                choices = c("Yes", "No"),
+                choices = c("Yes" = TRUE, "No" = FALSE),
                 selected = initial_raster,
                 inline = TRUE
               )
@@ -928,7 +942,7 @@ ui <- fluidPage(
                 inputId = "pt_size2",
                 label = "Point size",
                 value = 1,
-                min = 0.5,
+                min = 0.1,
                 max = 10,
                 step = 0.5,
                 width = "150px"
@@ -965,7 +979,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "arrange2",
                 label = "Arrange by",
-                choices = c("Row", "Column"),
+                choices = c("Row" = TRUE, "Column" = FALSE),
                 selected = initial_arrange
               )
             )
@@ -1080,7 +1094,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "label3",
                 label = "Label",
-                choices = c("Yes", "No"),
+                choices = c("Yes" = TRUE, "No" = FALSE),
                 selected = initial_label,
                 inline = TRUE
               )
@@ -1090,8 +1104,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "flip3",
                 label = "Flip",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1178,7 +1192,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "arrange3",
                 label = "Arrange by",
-                choices = c("Row", "Column"),
+                choices = c("Row" = TRUE, "Column" = FALSE),
                 selected = initial_arrange
               )
             )
@@ -1312,8 +1326,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "coExp4",
                 label = "Co-expression",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1322,8 +1336,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "stack4",
                 label = "Stack",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1332,8 +1346,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "flip4",
                 label = "Flip",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             )
@@ -1344,8 +1358,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "addbox4",
                 label = "Add box",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1354,8 +1368,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "addpoint4",
                 label = "Add point",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1364,8 +1378,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "addtrend4",
                 label = "Add trend",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             )
@@ -1414,8 +1428,8 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "sameylims4",
                 label = "Same y-axis",
-                choices = c("Yes", "No"),
-                selected = "No",
+                choices = c("Yes" = TRUE, "No" = FALSE),
+                selected = FALSE,
                 inline = TRUE
               )
             ),
@@ -1450,7 +1464,7 @@ ui <- fluidPage(
               radioButtons(
                 inputId = "arrange4",
                 label = "Arrange by",
-                choices = c("Row", "Column"),
+                choices = c("Row" = TRUE, "Column" = FALSE),
                 selected = initial_arrange
               )
             )
@@ -1523,7 +1537,7 @@ server <- function(input, output, session) {
     updateSelectInput(session, "reduction1", choices = reduction_name, selected = intersect(c(initial_reduction, default_reduction), reduction_name)[1])
     updateSelectInput(session, "group1", choices = meta_groups_name, selected = intersect(c(initial_group, "orig.ident"), meta_groups_name)[1])
     updateSelectInput(session, "split1", choices = c("None", meta_groups_name), selected = "None")
-    updateRadioButtons(session, "raster1", choices = c("Yes", "No"), selected = initial_raster)
+    updateRadioButtons(session, "raster1", choices = c("Yes" = TRUE, "No" = FALSE), selected = initial_raster)
   }) %>% bindEvent(input$dataset1, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
@@ -1548,7 +1562,7 @@ server <- function(input, output, session) {
       options = list(maxOptions = 20, maxItems = 20), server = TRUE
     )
     updateSelectInput(session, "split2", choices = c("None", meta_groups_name), selected = "None")
-    updateRadioButtons(session, "raster2", choices = c("Yes", "No"), selected = initial_raster)
+    updateRadioButtons(session, "raster2", choices = c("Yes" = TRUE, "No" = FALSE), selected = initial_raster)
   }) %>% bindEvent(input$dataset2, ignoreNULL = TRUE, ignoreInit = FALSE)
 
   observe({
@@ -1615,14 +1629,14 @@ server <- function(input, output, session) {
     } else {
       split1 <- input$split1
     }
-    label1 <- input$label1 == "Yes"
-    raster1 <- input$raster1 == "Yes"
+    label1 <- input$label1
+    raster1 <- input$raster1
     palette1 <- input$palette1
     theme1 <- input$theme1
     size1 <- input$size1
     pt_size1 <- input$pt_size1
     ncol1 <- input$ncol1
-    byrow1 <- input$arrange1 == "Row"
+    byrow1 <- input$arrange1
 
     # lapply(grep("1$",names(input),value = TRUE), function(x)print(paste0(x,":",input[[x]])))
 
@@ -1755,15 +1769,15 @@ server <- function(input, output, session) {
     slots2 <- input$slots2
     features2 <- input$features2
     feature_area2 <- input$feature_area2
-    coExp2 <- input$coExp2 == "Yes"
+    coExp2 <- input$coExp2
     scale2 <- input$scale2
-    raster2 <- input$raster2 == "Yes"
+    raster2 <- input$raster2
     palette2 <- input$palette2
     theme2 <- input$theme2
     size2 <- input$size2
     pt_size2 <- input$pt_size2
     ncol2 <- input$ncol2
-    byrow2 <- input$arrange2 == "Row"
+    byrow2 <- input$arrange2
 
     # lapply(grep("2$",names(input),value = TRUE), function(x)print(paste0(x,":",input[[x]])))
 
@@ -1812,7 +1826,7 @@ server <- function(input, output, session) {
         if (isTRUE(plot3d)) {
           p2_3d <- SCP::FeatureDimPlot3D(
             srt = srt_tmp, features = features2, reduction = reduction2, pt.size = pt_size2 * 2,
-            calculate_coexp = ifelse(coExp2 == "Yes", TRUE, FALSE), force = TRUE
+            calculate_coexp = coExp2, force = TRUE
           )
         } else {
           p2_3d <- NULL
@@ -1918,14 +1932,14 @@ server <- function(input, output, session) {
     } else {
       split3 <- input$split3
     }
-    label3 <- input$label3 == "Yes"
-    flip3 <- input$flip3 == "Yes"
+    label3 <- input$label3
+    flip3 <- input$flip3
     palette3 <- input$palette3
     theme3 <- input$theme3
     labelsize3 <- input$labelsize3
     size3 <- input$size3
     ncol3 <- input$ncol3
-    byrow3 <- input$arrange3 == "Row"
+    byrow3 <- input$arrange3
     if (input$aspectratio3 == "auto") {
       aspect.ratio <- NULL
     } else {
@@ -2067,18 +2081,18 @@ server <- function(input, output, session) {
     feature_area4 <- input$feature_area4
     plotby4 <- input$plotby4
     fillby4 <- input$fillby4
-    coExp4 <- input$coExp4 == "Yes"
-    stack4 <- input$stack4 == "Yes"
-    flip4 <- input$flip4 == "Yes"
-    addbox4 <- input$addbox4 == "Yes"
-    addpoint4 <- input$addpoint4 == "Yes"
-    addtrend4 <- input$addtrend4 == "Yes"
+    coExp4 <- input$coExp4
+    stack4 <- input$stack4
+    flip4 <- input$flip4
+    addbox4 <- input$addbox4
+    addpoint4 <- input$addpoint4
+    addtrend4 <- input$addtrend4
     palette4 <- input$palette4
     theme4 <- input$theme4
-    sameylims4 <- input$sameylims4 == "Yes"
+    sameylims4 <- input$sameylims4
     size4 <- input$size4
     ncol4 <- input$ncol4
-    byrow4 <- input$arrange4 == "Row"
+    byrow4 <- input$arrange4
     if (input$aspectratio4 == "auto") {
       aspect.ratio <- NULL
     } else {
diff --git a/R/SCP-cell_annotation.R b/R/SCP-cell_annotation.R
index bfef9bff..4ac82383 100644
--- a/R/SCP-cell_annotation.R
+++ b/R/SCP-cell_annotation.R
@@ -276,7 +276,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
   }
 
   if (!inherits(ref, "matrix")) {
-    ref <- as.matrix(ref)
+    ref <- as_matrix(ref)
   }
   k <- min(c(k, nrow(ref)))
 
@@ -321,7 +321,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
   # rownames(tst.expr) <- rownames(ref)
   # colnames(tst.expr) <- colnames(query)
   # features_common <- intersect(rownames(query), rownames(ref.expr))
-  # tst.expr[features_common, ] <- as.matrix(query[features_common, ])
+  # tst.expr[features_common, ] <- as_matrix(query[features_common, ])
   #
   # library(RcppArmadillo)
   # library(RcppXPtrUtils)
@@ -335,7 +335,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
   # }",
   #     depends = c("RcppArmadillo")
   #   )
-  #   cors <- as.matrix(parDist(t(query), method = "custom", func = CosineCPP))
+  #   cors <- as_matrix(parDist(t(query), method = "custom", func = CosineCPP))
   #   cors <- cors[colnames(ref.expr), colnames(tst.expr)]
   #
 
@@ -407,11 +407,11 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
       )
     }
     if (k == 1) {
-      match_k_cell <- as.matrix(apply(d, 2, function(x) names(x)[order(x, decreasing = FALSE)[1]]))
-      match_k_distance <- as.matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1]]))
+      match_k_cell <- as_matrix(apply(d, 2, function(x) names(x)[order(x, decreasing = FALSE)[1]]))
+      match_k_distance <- as_matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1]]))
     } else {
-      match_k_cell <- t(as.matrix(apply(d, 2, function(x) names(x)[order(x, decreasing = FALSE)[1:k]])))
-      match_k_distance <- t(as.matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1:k]])))
+      match_k_cell <- t(as_matrix(apply(d, 2, function(x) names(x)[order(x, decreasing = FALSE)[1:k]])))
+      match_k_distance <- t(as_matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1:k]])))
     }
   }
 
@@ -438,7 +438,7 @@ RunKNNPredict <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
         x <- x / sum(x)
         return(x)
       }))
-      match_prob <- as.matrix(match_prob)
+      match_prob <- as_matrix(match_prob)
       rownames(match_prob) <- names(match_freq)
       match_best <- apply(match_prob, 1, function(x) names(x)[order(x, decreasing = TRUE)][1])
     }
diff --git a/R/SCP-cellqc.R b/R/SCP-cellqc.R
index 00036637..c716d3b8 100644
--- a/R/SCP-cellqc.R
+++ b/R/SCP-cellqc.R
@@ -96,7 +96,7 @@ db_Scrublet <- function(srt, assay = "RNA", db_rate = ncol(srt) / 1000 * 0.01, .
   }
   check_Python("scrublet")
   scr <- import("scrublet")
-  raw_counts <- t(as.matrix(GetAssayData(object = srt, assay = assay, slot = "counts")))
+  raw_counts <- t(as_matrix(GetAssayData(object = srt, assay = assay, slot = "counts")))
   scrub <- scr$Scrublet(raw_counts, expected_doublet_rate = db_rate, ...)
   res <- scrub$scrub_doublets()
   doublet_scores <- res[[1]]
diff --git a/R/SCP-plot.R b/R/SCP-plot.R
index def37837..602d2a61 100644
--- a/R/SCP-plot.R
+++ b/R/SCP-plot.R
@@ -1548,7 +1548,7 @@ CellDimPlot <- function(srt, group.by, reduction = NULL, dims = c(1, 2), split.b
       density <- NULL
     }
     if (!is.null(graph)) {
-      net_mat <- as.matrix(x = graph)[rownames(dat), rownames(dat)]
+      net_mat <- as_matrix(graph)[rownames(dat), rownames(dat)]
       net_mat[net_mat == 0] <- NA
       net_mat[upper.tri(net_mat)] <- NA
       net_df <- reshape2::melt(net_mat, na.rm = TRUE, stringsAsFactors = FALSE)
@@ -2098,24 +2098,24 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
 
   if (length(features_gene) > 0) {
     if (all(rownames(srt@assays[[assay]]) %in% features_gene)) {
-      dat_gene <- t(slot(srt@assays[[assay]], slot))
+      dat_gene <- t(as_matrix(slot(srt@assays[[assay]], slot)))
     } else {
-      dat_gene <- t(slot(srt@assays[[assay]], slot)[features_gene, , drop = FALSE])
+      dat_gene <- t(as_matrix(slot(srt@assays[[assay]], slot)[features_gene, , drop = FALSE]))
     }
   } else {
     dat_gene <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_meta) > 0) {
-    dat_meta <- as.matrix(srt@meta.data[, features_meta, drop = FALSE])
+    dat_meta <- as_matrix(srt@meta.data[, features_meta, drop = FALSE])
   } else {
     dat_meta <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_embedding) > 0) {
-    dat_embedding <- as.matrix(FetchData(srt, vars = features_embedding))
+    dat_embedding <- as_matrix(FetchData(srt, vars = features_embedding))
   } else {
     dat_embedding <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
-  dat_exp <- do.call(cbind, list(dat_gene, dat_meta, dat_embedding))
+  dat_exp <- as_matrix(do.call(cbind, list(dat_gene, dat_meta, dat_embedding)))
   features <- unique(features[features %in% c(features_gene, features_meta, features_embedding)])
 
   if (!is.numeric(dat_exp) && !inherits(dat_exp, "Matrix")) {
@@ -2263,7 +2263,7 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
         cells.highlight_use <- rownames(dat)[dat[["color_blend"]] != bg_color]
       }
       if (!is.null(graph)) {
-        net_mat <- as.matrix(x = graph)[rownames(dat), rownames(dat)]
+        net_mat <- as_matrix(graph)[rownames(dat), rownames(dat)]
         net_mat[net_mat == 0] <- NA
         net_mat[upper.tri(net_mat)] <- NA
         net_df <- melt(net_mat, na.rm = TRUE, stringsAsFactors = FALSE)
@@ -2534,7 +2534,7 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
             colors_value <- seq(lower_cutoff %||% quantile(dat_exp[is.finite(dat_exp[, f]), f], lower_quantile, na.rm = TRUE), upper_cutoff %||% quantile(dat_exp[is.finite(dat_exp[, f]), f], upper_quantile, na.rm = TRUE) + 0.001, length.out = 100)
           }
           if (keep_scale == "all") {
-            all_values <- as.matrix(dat_exp[, features])
+            all_values <- as_matrix(dat_exp[, features])
             colors_value <- seq(lower_cutoff %||% quantile(all_values[is.finite(all_values)], lower_quantile, na.rm = TRUE), upper_cutoff %||% quantile(all_values, upper_quantile, na.rm = TRUE) + 0.001, length.out = 100)
           }
         }
@@ -2542,7 +2542,7 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
       dat[which(dat[, "value"] > max(colors_value, na.rm = TRUE)), "value"] <- max(colors_value, na.rm = TRUE)
       dat[which(dat[, "value"] < min(colors_value, na.rm = TRUE)), "value"] <- min(colors_value, na.rm = TRUE)
       if (!is.null(graph)) {
-        net_mat <- as.matrix(x = graph)[rownames(dat), rownames(dat)]
+        net_mat <- as_matrix(graph)[rownames(dat), rownames(dat)]
         net_mat[net_mat == 0] <- NA
         net_mat[upper.tri(net_mat)] <- NA
         net_df <- melt(net_mat, na.rm = TRUE, stringsAsFactors = FALSE)
@@ -3002,6 +3002,7 @@ CellDimPlot3D <- function(srt, group.by, reduction = NULL, dims = c(1, 2, 3), ax
 #' FeatureDimPlot3D(pancreas_sub, features = c("StandardPC_1", "StandardPC_2"), reduction = "StandardpcaUMAP3D")
 #'
 #' @importFrom Seurat Reductions Embeddings Key FetchData
+#' @importFrom Matrix t
 #' @importFrom methods slot
 #' @importFrom utils askYesNo
 #' @importFrom plotly plot_ly add_trace layout as_widget
@@ -3111,24 +3112,24 @@ FeatureDimPlot3D <- function(srt, features, reduction = NULL, dims = c(1, 2, 3),
 
   if (length(features_gene) > 0) {
     if (all(rownames(srt@assays[[assay]]) %in% features_gene)) {
-      dat_gene <- t(slot(srt@assays[[assay]], slot))
+      dat_gene <- t(as_matrix(slot(srt@assays[[assay]], slot)))
     } else {
-      dat_gene <- t(slot(srt@assays[[assay]], slot)[features_gene, , drop = FALSE])
+      dat_gene <- t(as_matrix(slot(srt@assays[[assay]], slot)[features_gene, , drop = FALSE]))
     }
   } else {
     dat_gene <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_meta) > 0) {
-    dat_meta <- as.matrix(srt@meta.data[, features_meta, drop = FALSE])
+    dat_meta <- as_matrix(srt@meta.data[, features_meta, drop = FALSE])
   } else {
     dat_meta <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_embedding) > 0) {
-    dat_embedding <- as.matrix(FetchData(srt, vars = features_embedding))
+    dat_embedding <- as_matrix(FetchData(srt, vars = features_embedding))
   } else {
     dat_embedding <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
-  dat_exp <- do.call(cbind, list(dat_gene, dat_meta, dat_embedding))
+  dat_exp <- as_matrix(do.call(cbind, list(dat_gene, dat_meta, dat_embedding)))
   features <- unique(features[features %in% c(features_gene, features_meta, features_embedding)])
 
   if (!is.numeric(dat_exp) && !inherits(dat_exp, "Matrix")) {
@@ -3429,6 +3430,7 @@ FeatureDimPlot3D <- function(srt, features, reduction = NULL, dims = c(1, 2, 3),
 #'   group.by = "SubCellType", bg.by = "CellType", stack = TRUE, flip = TRUE
 #' ) %>% panel_fix_overall(width = 8, height = 5) # As the plot is created by combining, we can adjust the overall height and width directly.
 #'
+#' FeatureStatPlot(pancreas_sub, stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "group")
 #' FeatureStatPlot(pancreas_sub, stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "feature")
 #' FeatureStatPlot(pancreas_sub,
 #'   stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "feature",
@@ -3449,7 +3451,7 @@ FeatureDimPlot3D <- function(srt, features, reduction = NULL, dims = c(1, 2, 3),
 #'
 #' library(Matrix)
 #' data <- pancreas_sub@assays$RNA@data
-#' pancreas_sub@assays$RNA@scale.data <- as.matrix(data / rowMeans(data))
+#' pancreas_sub@assays$RNA@scale.data <- as_matrix(data / rowMeans(data))
 #' FeatureStatPlot(pancreas_sub,
 #'   stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType",
 #'   slot = "scale.data", ylab = "FoldChange", same.y.lims = TRUE, y.max = 4
@@ -3467,7 +3469,7 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
                             palette = "Paired", palcolor = NULL, alpha = 1,
                             bg_palette = "Paired", bg_palcolor = NULL, bg_alpha = 0.2,
                             add_box = FALSE, box_color = "black", box_width = 0.1, box_ptsize = 2,
-                            add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5, jitter.height = 0.1,
+                            add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.4, jitter.height = 0.1,
                             add_trend = FALSE, trend_color = "black", trend_linewidth = 1, trend_ptsize = 2,
                             add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1,
                             cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
@@ -3663,7 +3665,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
                                palette = "Paired", palcolor = NULL, alpha = 1,
                                bg_palette = "Paired", bg_palcolor = NULL, bg_alpha = 0.2,
                                add_box = FALSE, box_color = "black", box_width = 0.1, box_ptsize = 2,
-                               add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.5, jitter.height = 0.1,
+                               add_point = FALSE, pt.color = "grey30", pt.size = NULL, pt.alpha = 1, jitter.width = 0.4, jitter.height = 0.1,
                                add_trend = FALSE, trend_color = "black", trend_linewidth = 1, trend_ptsize = 2,
                                add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1,
                                cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
@@ -3811,7 +3813,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
     dat_gene <- matrix(nrow = length(allcells), ncol = 0)
   }
   if (length(features_meta) > 0) {
-    dat_meta <- as.matrix(meta.data[, features_meta, drop = FALSE])
+    dat_meta <- as_matrix(meta.data[, features_meta, drop = FALSE])
   } else {
     dat_meta <- matrix(nrow = length(allcells), ncol = 0)
   }
@@ -3846,7 +3848,7 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
   }
 
   if (isTRUE(same.y.lims)) {
-    valus <- as.matrix(dat_use[, stat.by, drop = FALSE])[is.finite(as.matrix(dat_use[, stat.by, drop = FALSE]))]
+    valus <- as_matrix(dat_use[, stat.by, drop = FALSE])[is.finite(as_matrix(dat_use[, stat.by, drop = FALSE]))]
     if (is.null(y.max)) {
       y.max <- max(valus, na.rm = TRUE)
     } else if (is.character(y.max)) {
@@ -5241,7 +5243,7 @@ FeatureCorPlot <- function(srt, features, group.by = NULL, split.by = NULL, cell
     dat_gene <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_meta) > 0) {
-    dat_meta <- as.matrix(srt@meta.data[, features_meta, drop = FALSE])
+    dat_meta <- as_matrix(srt@meta.data[, features_meta, drop = FALSE])
   } else {
     dat_meta <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
@@ -5255,7 +5257,7 @@ FeatureCorPlot <- function(srt, features, group.by = NULL, split.by = NULL, cell
     stop("'features' must be type of numeric variable.")
   }
   if (!inherits(dat_exp, "dgCMatrix")) {
-    dat_exp <- as.sparse(as.matrix(dat_exp))
+    dat_exp <- as.sparse(as_matrix(dat_exp))
   }
   if (length(features) > 10 && !isTRUE(force)) {
     warning("More than 10 features to be paired compared which will generate more than 50 plots.", immediate. = TRUE)
@@ -5664,7 +5666,7 @@ CellDensityPlot <- function(srt, features, group.by = NULL, split.by = NULL, ass
     dat_gene <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
   if (length(features_meta) > 0) {
-    dat_meta <- as.matrix(srt@meta.data[, features_meta, drop = FALSE])
+    dat_meta <- as_matrix(srt@meta.data[, features_meta, drop = FALSE])
   } else {
     dat_meta <- matrix(nrow = ncol(srt@assays[[1]]), ncol = 0)
   }
@@ -5688,10 +5690,10 @@ CellDensityPlot <- function(srt, features, group.by = NULL, split.by = NULL, ass
   }
 
   if (isTRUE(same.y.lims) && is.null(y.max)) {
-    y.max <- max(as.matrix(dat_exp[, features])[is.finite(as.matrix(dat_exp[, features]))], na.rm = TRUE)
+    y.max <- max(as_matrix(dat_exp[, features])[is.finite(as_matrix(dat_exp[, features]))], na.rm = TRUE)
   }
   if (isTRUE(same.y.lims) && is.null(y.min)) {
-    y.min <- min(as.matrix(dat_exp[, features])[is.finite(as.matrix(dat_exp[, features]))], na.rm = TRUE)
+    y.min <- min(as_matrix(dat_exp[, features])[is.finite(as_matrix(dat_exp[, features]))], na.rm = TRUE)
   }
 
   plist <- list()
@@ -6119,7 +6121,7 @@ PAGAPlot <- function(srt, paga = srt@misc$paga, type = "connectivities",
   }
 
   out <- GraphPlot(
-    node = dat, edge = as.matrix(connectivities), node_coord = paste0(reduction_key, dims),
+    node = dat, edge = as_matrix(connectivities), node_coord = paste0(reduction_key, dims),
     node_group = groups, node_palette = node_palette, node_palcolor = node_palcolor, node_size = node_size, node_alpha = node_alpha,
     node_highlight = node_highlight, node_highlight_color = node_highlight_color,
     label = label, label.size = label.size, label.fg = label.fg, label.bg = label.bg, label.bg.r = label.bg.r,
@@ -6391,7 +6393,7 @@ GraphPlot <- function(node, edge, transition = NULL,
   }
 
   if (!is.null(transition)) {
-    trans2 <- trans1 <- as.matrix(transition)
+    trans2 <- trans1 <- as_matrix(transition)
     trans1[lower.tri(trans1)] <- 0
     trans2[upper.tri(trans2)] <- 0
     trans <- t(trans1) - trans2
@@ -6910,7 +6912,7 @@ compute_velocity_on_grid <- function(X_emb, V_emb,
     gr <- seq(m, M, length.out = ceiling(50 * density))
     grs <- c(grs, list(gr))
   }
-  X_grid <- as.matrix(expand.grid(grs))
+  X_grid <- as_matrix(expand.grid(grs))
 
   d <- dist(
     x = as.sparse(X_emb),
@@ -6918,8 +6920,8 @@ compute_velocity_on_grid <- function(X_emb, V_emb,
     method = "euclidean",
     use_nan = TRUE
   )
-  neighbors <- t(as.matrix(apply(d, 2, function(x) order(x, decreasing = FALSE)[1:n_neighbors])))
-  dists <- t(as.matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1:n_neighbors]])))
+  neighbors <- t(as_matrix(apply(d, 2, function(x) order(x, decreasing = FALSE)[1:n_neighbors])))
+  dists <- t(as_matrix(apply(d, 2, function(x) x[order(x, decreasing = FALSE)[1:n_neighbors]])))
 
   # ggplot() +
   #   annotate(geom = "point", x = X_grid[, 1], y = X_grid[, 2]) +
@@ -7753,8 +7755,7 @@ mestimate <- function(data) {
 #'     "Rbp4", "Pyy", # Endocrine
 #'     "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
 #'   ),
-#'   group.by = c("CellType", "SubCellType"),
-#'   show_row_names = TRUE
+#'   group.by = c("CellType", "SubCellType")
 #' )
 #' ht1$plot
 #' panel_fix(ht1$plot, height = 4, width = 6, raster = TRUE, dpi = 50)
@@ -7765,14 +7766,12 @@ mestimate <- function(data) {
 #' ht2 <- GroupHeatmap(
 #'   srt = pancreas_sub, features = de_filter$gene, group.by = "CellType",
 #'   split.by = "Phase", cell_split_palette = "Dark2",
-#'   cluster_rows = TRUE, cluster_columns = TRUE,
-#'   nlabel = 10, show_row_names = FALSE
+#'   cluster_rows = TRUE, cluster_columns = TRUE
 #' )
 #' ht2$plot
 #'
 #' ht3 <- GroupHeatmap(
 #'   srt = pancreas_sub, features = de_filter$gene, feature_split = de_filter$group1, group.by = "CellType",
-#'   nlabel = 20, show_row_names = FALSE,
 #'   species = "Mus_musculus", db = "GO_BP", anno_terms = TRUE, anno_keys = TRUE, anno_features = TRUE
 #' )
 #' ht3$plot
@@ -7787,10 +7786,10 @@ mestimate <- function(data) {
 #'   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
 #'   heatmap_palette = "YlOrRd",
 #'   cell_annotation = c("Phase", "G2M_score", "Neurod2"), cell_annotation_palette = c("Dark2", "Paired", "Paired"),
-#'   cell_annotation_params = list(height = grid::unit(0.5, "in")),
+#'   cell_annotation_params = list(height = grid::unit(20, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
-#'   add_dot = TRUE, add_bg = TRUE, show_row_names = TRUE
+#'   add_dot = TRUE, add_bg = TRUE, nlabel = 0, show_row_names = TRUE
 #' )
 #' ht4$plot
 #'
@@ -7798,25 +7797,25 @@ mestimate <- function(data) {
 #'   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
 #'   heatmap_palette = "YlOrRd",
 #'   cell_annotation = c("Phase", "G2M_score", "Neurod2"), cell_annotation_palette = c("Dark2", "Paired", "Paired"),
-#'   cell_annotation_params = list(width = grid::unit(0.5, "in")),
+#'   cell_annotation_params = list(width = grid::unit(20, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   add_dot = TRUE, add_bg = TRUE,
-#'   flip = TRUE, column_title_rot = 45, show_column_names = TRUE
+#'   flip = TRUE, column_title_rot = 45, nlabel = 0, show_row_names = TRUE
 #' )
 #' ht5$plot
 #'
 #' ht6 <- GroupHeatmap(pancreas_sub,
 #'   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
 #'   add_violin = TRUE, cluster_rows = TRUE,
-#'   show_row_names = TRUE
+#'   nlabel = 0, show_row_names = TRUE
 #' )
 #' ht6$plot
 #'
 #' ht7 <- GroupHeatmap(pancreas_sub,
 #'   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
 #'   add_violin = TRUE, fill.by = "expression", fill_palette = "Blues", cluster_rows = TRUE,
-#'   show_row_names = TRUE
+#'   nlabel = 0, show_row_names = TRUE
 #' )
 #' ht7$plot
 #'
@@ -7824,7 +7823,8 @@ mestimate <- function(data) {
 #'   features = de_top$gene, group.by = "CellType", split.by = "Phase", n_split = 4,
 #'   cluster_rows = TRUE, cluster_columns = TRUE, cluster_row_slices = TRUE, cluster_column_slices = TRUE,
 #'   add_dot = TRUE, add_reticle = TRUE, heatmap_palette = "viridis",
-#'   show_row_names = TRUE, ht_params = list(row_gap = grid::unit(0, "mm"), row_names_gp = grid::gpar(fontsize = 10))
+#'   nlabel = 0, show_row_names = TRUE,
+#'   ht_params = list(row_gap = grid::unit(0, "mm"), row_names_gp = grid::gpar(fontsize = 10))
 #' )
 #' ht8$plot
 #'
@@ -7862,8 +7862,8 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
                          add_violin = FALSE, fill.by = "feature", fill_palette = "Dark2", fill_palcolor = NULL,
                          heatmap_palette = "RdBu", heatmap_palcolor = NULL, group_palette = "Paired", group_palcolor = NULL,
                          cell_split_palette = "simspec", cell_split_palcolor = NULL, feature_split_palette = "simspec", feature_split_palcolor = NULL,
-                         cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = if (flip) list(width = grid::unit(1, "cm")) else list(height = grid::unit(1, "cm")),
-                         feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = list(),
+                         cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else list(height = grid::unit(20, "mm")),
+                         feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else list(width = grid::unit(5, "mm")),
                          use_raster = NULL, raster_device = "png", raster_by_magick = FALSE, height = NULL, width = NULL, units = "inch",
                          seed = 11, ht_params = list()) {
   set.seed(seed)
@@ -8083,7 +8083,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
   gene_unique <- features_unique[features %in% rownames(srt@assays[[assay]])]
   meta <- features[features %in% colnames(srt@meta.data)]
 
-  mat_raw <- as.matrix(rbind(slot(srt@assays[[assay]], slot)[gene, cells, drop = FALSE], t(srt@meta.data[cells, meta, drop = FALSE])))[features, , drop = FALSE]
+  mat_raw <- as_matrix(rbind(slot(srt@assays[[assay]], slot)[gene, cells, drop = FALSE], t(srt@meta.data[cells, meta, drop = FALSE])))[features, , drop = FALSE]
   rownames(mat_raw) <- features_unique
   if (isTRUE(lib_normalize) && min(mat_raw, na.rm = TRUE) >= 0) {
     if (!is.null(libsize)) {
@@ -8309,8 +8309,8 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
           subplots <- CellStatPlot(srt,
             flip = flip,
             cells = names(cell_groups[[cell_group]]), plot_type = "pie",
-            group.by = cell_group, stat.by = cellan, split.by = split.by,
-            palette = palette, palcolor = palcolor,
+            stat.by = cellan, group.by = cell_group, split.by = split.by,
+            palette = palette, palcolor = palcolor, title = NULL,
             individual = TRUE, combine = FALSE
           )
           subplots_list[[paste0(cellan, ":", cell_group)]] <- subplots
@@ -8318,7 +8318,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", cell_group, "-", nm), "';
               grid.draw(g)
               "
@@ -8374,7 +8374,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", cell_group, "-", nm), "';
               grid.draw(g)
               "
@@ -8710,7 +8710,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
       # legend <- get_legend(vlnplots[[1]])
       # funbody <- paste0(
       #   "
-      #         g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+      #         g <- as_grob(subplots_list[['", cellan, ":", cell_group, "']]", "[['", nm, "']] + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
       #         grid.draw(g)
       #         "
       # )
@@ -9063,8 +9063,8 @@ FeatureHeatmap <- function(srt, features = NULL, cells = NULL, group.by = NULL,
                            nlabel = 20, features_label = NULL, label_size = 10, label_color = "black",
                            heatmap_palette = "RdBu", heatmap_palcolor = NULL, group_palette = "Paired", group_palcolor = NULL,
                            cell_split_palette = "simspec", cell_split_palcolor = NULL, feature_split_palette = "simspec", feature_split_palcolor = NULL,
-                           cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = list(),
-                           feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = list(),
+                           cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = if (flip) list(width = grid::unit(5, "mm")) else list(height = grid::unit(5, "mm")),
+                           feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else list(width = grid::unit(5, "mm")),
                            use_raster = NULL, raster_device = "png", raster_by_magick = FALSE, height = NULL, width = NULL, units = "inch",
                            seed = 11, ht_params = list()) {
   set.seed(seed)
@@ -9270,7 +9270,7 @@ FeatureHeatmap <- function(srt, features = NULL, cells = NULL, group.by = NULL,
   gene_unique <- features_unique[features %in% rownames(srt@assays[[assay]])]
   meta <- features[features %in% colnames(srt@meta.data)]
   all_cells <- unique(unlist(lapply(cell_groups, names)))
-  mat_raw <- as.matrix(rbind(slot(srt@assays[[assay]], slot)[gene, all_cells, drop = FALSE], t(srt@meta.data[all_cells, meta, drop = FALSE])))[features, , drop = FALSE]
+  mat_raw <- as_matrix(rbind(slot(srt@assays[[assay]], slot)[gene, all_cells, drop = FALSE], t(srt@meta.data[all_cells, meta, drop = FALSE])))[features, , drop = FALSE]
   rownames(mat_raw) <- features_unique
   if (isTRUE(lib_normalize) && min(mat_raw, na.rm = TRUE) >= 0) {
     if (!is.null(libsize)) {
@@ -10016,7 +10016,7 @@ FeatureCorHeatmap <- function(srt, features, cells) {
 #'   query_group = "SubCellType", ref_group = "celltype",
 #'   query_cell_annotation = "Phase", query_cell_annotation_palette = "Set2",
 #'   ref_cell_annotation = "tech", ref_cell_annotation_palette = "Set3",
-#'   width = 3, height = 2
+#'   width = 4, height = 4
 #' )
 #' ht2$plot
 #'
@@ -10064,8 +10064,8 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
                            heatmap_palette = "RdBu", heatmap_palcolor = NULL,
                            query_group_palette = "Paired", query_group_palcolor = NULL,
                            ref_group_palette = "simspec", ref_group_palcolor = NULL,
-                           query_cell_annotation = NULL, query_cell_annotation_palette = "Paired", query_cell_annotation_palcolor = NULL, query_cell_annotation_params = if (flip) list(height = grid::unit(1, "cm")) else list(width = grid::unit(1, "cm")),
-                           ref_cell_annotation = NULL, ref_cell_annotation_palette = "Paired", ref_cell_annotation_palcolor = NULL, ref_cell_annotation_params = if (flip) list(width = grid::unit(1, "cm")) else list(height = grid::unit(1, "cm")),
+                           query_cell_annotation = NULL, query_cell_annotation_palette = "Paired", query_cell_annotation_palcolor = NULL, query_cell_annotation_params = if (flip) list(height = grid::unit(20, "mm")) else list(width = grid::unit(20, "mm")),
+                           ref_cell_annotation = NULL, ref_cell_annotation_palette = "Paired", ref_cell_annotation_palcolor = NULL, ref_cell_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else list(height = grid::unit(20, "mm")),
                            use_raster = NULL, raster_device = "png", raster_by_magick = FALSE, height = NULL, width = NULL, units = "inch",
                            seed = 11, ht_params = list()) {
   set.seed(seed)
@@ -10127,10 +10127,10 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
   distance_matrix <- srt_query@tools[[paste0(prefix, "_classification")]][["distance_matrix"]]
   distance_metric <- srt_query@tools[[paste0(prefix, "_classification")]][["distance_metric"]]
   if (distance_metric %in% simil_method) {
-    simil_matrix <- t(as.matrix(1 - distance_matrix))
+    simil_matrix <- t(as_matrix(1 - distance_matrix))
     simil_name <- paste0(capitalize(distance_metric), " similarity")
   } else if (distance_metric %in% dist_method) {
-    simil_matrix <- t(as.matrix(1 - distance_matrix / max(distance_matrix, na.rm = TRUE)))
+    simil_matrix <- t(as_matrix(1 - distance_matrix / max(distance_matrix, na.rm = TRUE)))
     simil_name <- paste0("1-dist[", distance_metric, "]/max(dist[", distance_metric, "])")
   }
   simil_matrix[is.infinite(simil_matrix)] <- max(abs(simil_matrix[!is.infinite(simil_matrix)]), na.rm = TRUE) * ifelse(simil_matrix[is.infinite(simil_matrix)] > 0, 1, -1)
@@ -10345,7 +10345,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(query_subplots_list[['", cellan, ":", query_group, "']]", "[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(query_subplots_list[['", cellan, ":", query_group, "']]", "[['", nm, "']] + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", query_group, "-", nm), "';
               grid.draw(g)
               "
@@ -10423,7 +10423,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(query_subplots_list[['", cellan, ":", query_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(query_subplots_list[['", cellan, ":", query_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", query_group, "-", nm), "';
               grid.draw(g)
               "
@@ -10518,7 +10518,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(ref_subplots_list[['", cellan, ":", ref_group, "']]", "[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(ref_subplots_list[['", cellan, ":", ref_group, "']]", "[['", nm, "']] + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", ref_group, "-", nm), "';
               grid.draw(g)
               "
@@ -10596,7 +10596,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
           for (nm in names(subplots)) {
             funbody <- paste0(
               "
-              g <- as_grob(ref_subplots_list[['", cellan, ":", ref_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(legend.position = 'none'));
+              g <- as_grob(ref_subplots_list[['", cellan, ":", ref_group, "']]", "[['", nm, "']]  + facet_null() + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
               g$name <- '", paste0(cellan, ":", ref_group, "-", nm), "';
               grid.draw(g)
               "
@@ -10892,7 +10892,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
 #'   cell_annotation_palette = c("Paired", "simspec", "Purples"),
 #'   separate_annotation = list("SubCellType", c("Nnat", "Irx1")),
 #'   separate_annotation_palette = c("Paired", "Set1"),
-#'   separate_annotation_params = list(height = grid::unit(2, "cm")),
+#'   separate_annotation_params = list(height = grid::unit(20, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   pseudotime_label = 25,
@@ -10912,7 +10912,7 @@ CellCorHeatmap <- function(srt_query, srt_ref = NULL, bulk_ref = NULL,
 #'   cell_annotation_palette = c("Paired", "simspec", "Purples"),
 #'   separate_annotation = list("SubCellType", c("Nnat", "Irx1")),
 #'   separate_annotation_palette = c("Paired", "Set1"),
-#'   separate_annotation_params = list(width = grid::unit(2, "cm")),
+#'   separate_annotation_params = list(width = grid::unit(20, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   pseudotime_label = 25,
@@ -10967,9 +10967,9 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
                            heatmap_palette = "viridis", heatmap_palcolor = NULL,
                            pseudotime_palette = "cividis", pseudotime_palcolor = NULL,
                            feature_split_palette = "simspec", feature_split_palcolor = NULL,
-                           cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = list(),
-                           feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = list(),
-                           separate_annotation = NULL, separate_annotation_palette = "Paired", separate_annotation_palcolor = NULL, separate_annotation_params = if (flip) list(width = grid::unit(2, "cm")) else list(height = grid::unit(2, "cm")),
+                           cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = if (flip) list(width = grid::unit(5, "mm")) else list(height = grid::unit(5, "mm")),
+                           feature_annotation = NULL, feature_annotation_palette = "Dark2", feature_annotation_palcolor = NULL, feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else list(width = grid::unit(5, "mm")),
+                           separate_annotation = NULL, separate_annotation_palette = "Paired", separate_annotation_palcolor = NULL, separate_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else list(height = grid::unit(20, "mm")),
                            reverse_ht = NULL, use_raster = NULL, raster_device = "png", raster_by_magick = FALSE, height = NULL, width = NULL, units = "inch",
                            seed = 11, ht_params = list()) {
   set.seed(seed)
@@ -11208,7 +11208,7 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
     Y_libsize <- colSums(slot(srt@assays[[assay]], "counts"))
     for (l in lineages) {
       cells <- gsub(pattern = l, replacement = "", x = cell_order_list[[l]])
-      mat_tmp <- as.matrix(rbind(slot(srt@assays[[assay]], slot)[gene, cells, drop = FALSE], t(srt@meta.data[cells, meta, drop = FALSE])))[features, , drop = FALSE]
+      mat_tmp <- as_matrix(rbind(slot(srt@assays[[assay]], slot)[gene, cells, drop = FALSE], t(srt@meta.data[cells, meta, drop = FALSE])))[features, , drop = FALSE]
       if (isTRUE(lib_normalize) && min(mat_tmp, na.rm = TRUE) >= 0) {
         if (!is.null(libsize)) {
           libsize_use <- libsize
@@ -11375,7 +11375,7 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
           nm <- paste0(cellan, ":", l)
           funbody <- paste0(
             "
-            g <- as_grob(subplots_list[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+            g <- as_grob(subplots_list[['", nm, "']] + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
             g$name <- '", nm, "';
             grid.draw(g);
             grid.rect(gp = gpar(fill = 'transparent', col = 'black'));
@@ -11421,7 +11421,7 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
           nm <- paste0(paste0(cellan, collapse = ","), ":", l)
           funbody <- paste0(
             "
-            g <- as_grob(subplots_list[['", nm, "']] + theme_void() + theme(legend.position = 'none'));
+            g <- as_grob(subplots_list[['", nm, "']] + theme_void() + theme(plot.title = element_blank(), plot.subtitle = element_blank(), legend.position = 'none'));
             g$name <- '", nm, "';
             grid.draw(g);
             grid.rect(gp = gpar(fill = 'transparent', col = 'black'));
@@ -11650,8 +11650,8 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
       ha_list[[l]] <- anno_simple(
         x = is.na(feature_metadata[, paste0(l, order_by)]) + 0,
         col = c("0" = "#181830", "1" = "transparent"),
-        width = unit(0.5, "cm"),
-        height = unit(0.5, "cm"),
+        width = unit(5, "mm"),
+        height = unit(5, "mm"),
         which = ifelse(flip, "column", "row")
       )
     }
@@ -11802,9 +11802,7 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
   if ((!is.null(row_split) && length(index) > 0) || any(c(anno_terms, anno_keys, anno_features)) || !is.null(width) || !is.null(height)) {
     fix <- TRUE
     if (is.null(width) || is.null(height)) {
-      message("The size of the heatmap is fixed because certain elements are not scalable.\n
-              The width and height of the heatmap are determined by the size of the current viewport.\n
-              If you want to have more control over the size, you can manually set the parameters 'width' and 'height'.")
+      message("\nThe size of the heatmap is fixed because certain elements are not scalable.\nThe width and height of the heatmap are determined by the size of the current viewport.\nIf you want to have more control over the size, you can manually set the parameters 'width' and 'height'.\n")
     }
   } else {
     fix <- FALSE
@@ -12088,10 +12086,10 @@ DynamicPlot <- function(srt, lineages, features, group.by = NULL, cells = NULL,
       upr_matrix <- cbind(upr_matrix, srt_tmp@tools[[paste0("DynamicFeatures_", l)]][["upr_matrix"]][, feature_calcu, drop = FALSE])
       lwr_matrix <- cbind(lwr_matrix, srt_tmp@tools[[paste0("DynamicFeatures_", l)]][["lwr_matrix"]][, feature_calcu, drop = FALSE])
     }
-    raw_matrix_list[[l]] <- as.matrix(raw_matrix[, features, drop = FALSE])
-    fitted_matrix_list[[l]] <- as.matrix(fitted_matrix[, features, drop = FALSE])
-    upr_matrix_list[[l]] <- as.matrix(upr_matrix[, features, drop = FALSE])
-    lwr_matrix_list[[l]] <- as.matrix(lwr_matrix[, features, drop = FALSE])
+    raw_matrix_list[[l]] <- as_matrix(raw_matrix[, features, drop = FALSE])
+    fitted_matrix_list[[l]] <- as_matrix(fitted_matrix[, features, drop = FALSE])
+    upr_matrix_list[[l]] <- as_matrix(upr_matrix[, features, drop = FALSE])
+    lwr_matrix_list[[l]] <- as_matrix(lwr_matrix[, features, drop = FALSE])
     cell_union <- unique(c(cell_union, rownames(raw_matrix)))
   }
 
@@ -13394,7 +13392,7 @@ adjustlayout <- function(graph, layout, width, height = 2, scale = 100, iter = 1
   # }
 
   for (i in seq_len(iter)) {
-    dist_matrix <- as.matrix(dist(layout))
+    dist_matrix <- as_matrix(dist(layout))
     nearest_neighbors <- apply(dist_matrix, 2, function(x) which(x == min(x[x > 0])), simplify = FALSE)
     # nearest_neighbors <- apply(dist_matrix, 2, function(x) {
     #   head(order(x), 3)[-1]
diff --git a/R/SCP-workflow.R b/R/SCP-workflow.R
index 66165414..f6897fa2 100644
--- a/R/SCP-workflow.R
+++ b/R/SCP-workflow.R
@@ -1600,7 +1600,7 @@ scVI_integrate <- function(srtMerge = NULL, batch = NULL, append = TRUE, srtList
     model$train()
     srtIntegrated <- srtMerge
     srtMerge <- NULL
-    corrected <- t(as.matrix(model$get_normalized_expression()))
+    corrected <- t(as_matrix(model$get_normalized_expression()))
     srtIntegrated[["scVIcorrected"]] <- CreateAssayObject(counts = corrected)
     DefaultAssay(srtIntegrated) <- "scVIcorrected"
     VariableFeatures(srtIntegrated[["scVIcorrected"]]) <- HVF
@@ -1619,7 +1619,7 @@ scVI_integrate <- function(srtMerge = NULL, batch = NULL, append = TRUE, srtList
     srtMerge <- NULL
   }
 
-  latent <- as.matrix(model$get_latent_representation())
+  latent <- as_matrix(model$get_latent_representation())
   rownames(latent) <- colnames(srtIntegrated)
   colnames(latent) <- paste0("scVI_", seq_len(ncol(latent)))
   srtIntegrated[["scVI"]] <- CreateDimReducObject(embeddings = latent, key = "scVI_", assay = DefaultAssay(srtIntegrated))
@@ -1990,7 +1990,7 @@ fastMNN_integrate <- function(srtMerge = NULL, batch = NULL, append = TRUE, srtL
 
   srtIntegrated <- srtMerge
   srtMerge <- NULL
-  srtIntegrated[["fastMNNcorrected"]] <- CreateAssayObject(counts = as.matrix(out@assays@data$reconstructed))
+  srtIntegrated[["fastMNNcorrected"]] <- CreateAssayObject(counts = as_matrix(out@assays@data$reconstructed))
   DefaultAssay(srtIntegrated) <- "fastMNNcorrected"
   VariableFeatures(srtIntegrated[["fastMNNcorrected"]]) <- HVF
   reduction <- out@int_colData$reducedDims$corrected
@@ -2352,7 +2352,7 @@ Scanorama_integrate <- function(srtMerge = NULL, batch = NULL, append = TRUE, sr
   assaylist <- list()
   genelist <- list()
   for (i in seq_along(srtList)) {
-    assaylist[[i]] <- t(as.matrix(GetAssayData(object = srtList[[i]], slot = "data", assay = DefaultAssay(srtList[[i]]))[HVF, , drop = FALSE]))
+    assaylist[[i]] <- t(as_matrix(GetAssayData(object = srtList[[i]], slot = "data", assay = DefaultAssay(srtList[[i]]))[HVF, , drop = FALSE]))
     genelist[[i]] <- HVF
   }
   if (isTRUE(return_corrected)) {
diff --git a/R/Seurat-function.R b/R/Seurat-function.R
index a7b09cf7..460b7788 100644
--- a/R/Seurat-function.R
+++ b/R/Seurat-function.R
@@ -134,7 +134,7 @@ RunNMF.default <- function(object, assay = NULL, slot = "data", nbes = 50,
   if (nmf.method == "NMF") {
     check_R("NMF")
     seed <- NMF::seed
-    nmf.results <- NMF::nmf(x = as.matrix(t(object)), rank = nbes)
+    nmf.results <- NMF::nmf(x = as_matrix(t(object)), rank = nbes)
     cell.embeddings <- nmf.results@fit@W
     feature.loadings <- t(nmf.results@fit@H)
   }
@@ -271,7 +271,7 @@ RunMDS.default <- function(object, assay = NULL, slot = "data",
     object <- t(object)
   }
   nmds <- min(nmds, nrow(x = object) - 1)
-  x <- t(as.matrix(object))
+  x <- t(as_matrix(object))
   cell.dist <- as.dist(dist(x = x, method = dist.method))
   if (mds.method == "cmdscale") {
     mds.results <- cmdscale(cell.dist, k = nmds, eig = TRUE, ...)
@@ -402,8 +402,8 @@ RunGLMPCA.default <- function(object, assay = NULL, slot = "counts",
   fam <- match.arg(fam)
   glmpca_results <- glmpca::glmpca(Y = object, L = L, fam = fam, ...)
   glmpca_dimnames <- paste0(reduction.key, seq_len(L))
-  factors <- as.matrix(glmpca_results$factors)
-  loadings <- as.matrix(glmpca_results$loadings)
+  factors <- as_matrix(glmpca_results$factors)
+  loadings <- as_matrix(glmpca_results$loadings)
   colnames(x = factors) <- glmpca_dimnames
   colnames(x = loadings) <- glmpca_dimnames
   factors_l2_norm <- sqrt(colSums(factors^2))
@@ -471,7 +471,7 @@ RunDM.Seurat <- function(object,
                          verbose = TRUE, seed.use = 11, ...) {
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < ndcs) {
       stop("Please provide as many or more features than ndcs: ",
         length(x = features), " features provided, ",
@@ -523,7 +523,7 @@ RunDM.default <- function(object, assay = NULL, slot = "data",
     set.seed(seed = seed.use)
   }
 
-  dm.results <- destiny::DiffusionMap(data = as.matrix(object), n_eigs = ndcs, sigma = sigma, k = k, distance = dist.method, verbose = verbose, ...)
+  dm.results <- destiny::DiffusionMap(data = as_matrix(object), n_eigs = ndcs, sigma = sigma, k = k, distance = dist.method, verbose = verbose, ...)
 
   cell.embeddings <- dm.results@eigenvectors
   rownames(x = cell.embeddings) <- rownames(object)
@@ -599,7 +599,7 @@ RunUMAP2.Seurat <- function(object,
   }
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < n.components) {
       stop(
         "Please provide as many or more features than n.components: ",
@@ -611,7 +611,7 @@ RunUMAP2.Seurat <- function(object,
       )
     }
   } else if (!is.null(x = dims)) {
-    data.use <- as.matrix(Embeddings(object[[reduction]])[, dims])
+    data.use <- as_matrix(Embeddings(object[[reduction]])[, dims])
     assay <- DefaultAssay(object = object[[reduction]])
     if (length(x = dims) < n.components) {
       stop(
@@ -793,7 +793,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       } else {
         obs_sample <- 1:ncol(object)
       }
-      if (!isSymmetric(as.matrix(object[obs_sample, obs_sample]))) {
+      if (!isSymmetric(as_matrix(object[obs_sample, obs_sample]))) {
         stop("Graph must be a symmetric matrix.")
       }
 
@@ -810,7 +810,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       # if (inherits(object, what = "dgCMatrix")) {
       #   object <- as_matrix(object)
       # } else {
-      #   object <- as.matrix(object)
+      #   object <- as_matrix(object)
       # }
       # if (!isSymmetric(object)) {
       #   stop("Graph must be a symmetric matrix.")
@@ -941,7 +941,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       } else {
         obs_sample <- 1:ncol(object)
       }
-      if (!isSymmetric(as.matrix(object[obs_sample, obs_sample]))) {
+      if (!isSymmetric(as_matrix(object[obs_sample, obs_sample]))) {
         stop("Graph must be a symmetric matrix.")
       }
       val <- split(object@x, rep(1:ncol(object), diff(object@p)))
@@ -959,8 +959,8 @@ RunUMAP2.default <- function(object, assay = NULL,
       }, x = val, y = val))
       idx[is.na(idx)] <- sample(1:nrow(object), size = sum(is.na(idx)), replace = TRUE)
       nn <- list(idx = idx, dist = max(connectivity) - connectivity + min(diff(range(connectivity)), 1) / 1e50)
-      # idx <- t(as.matrix(apply(object, 2, function(x) order(x, decreasing = TRUE)[1:n.neighbors])))
-      # connectivity <- t(as.matrix(apply(object, 2, function(x) x[order(x, decreasing = TRUE)[1:n.neighbors]])))
+      # idx <- t(as_matrix(apply(object, 2, function(x) order(x, decreasing = TRUE)[1:n.neighbors])))
+      # connectivity <- t(as_matrix(apply(object, 2, function(x) x[order(x, decreasing = TRUE)[1:n.neighbors]])))
       out <- uwot::umap(
         X = NULL, nn_method = nn, n_threads = 1, n_components = n.components,
         metric = metric, n_epochs = n.epochs, learning_rate = learning.rate,
@@ -1080,8 +1080,8 @@ RunUMAP2.default <- function(object, assay = NULL,
       return(reduction)
     }
     if (inherits(x = object, what = "Graph")) {
-      match_k <- t(as.matrix(apply(object, 2, function(x) order(x, decreasing = TRUE)[1:n.neighbors])))
-      match_k_connectivity <- t(as.matrix(apply(object, 2, function(x) x[order(x, decreasing = TRUE)[1:n.neighbors]])))
+      match_k <- t(as_matrix(apply(object, 2, function(x) order(x, decreasing = TRUE)[1:n.neighbors])))
+      match_k_connectivity <- t(as_matrix(apply(object, 2, function(x) x[order(x, decreasing = TRUE)[1:n.neighbors]])))
       object <- list(idx = match_k, dist = max(match_k_connectivity) - match_k_connectivity)
       if (is.null(model$num_precomputed_nns) || model$num_precomputed_nns == 0) {
         model$num_precomputed_nns <- 1
@@ -1168,7 +1168,7 @@ RunPaCMAP.Seurat <- function(object, reduction = "pca", dims = NULL, features =
   }
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < n_components) {
       stop(
         "Please provide as many or more features than n_components: ",
@@ -1297,7 +1297,7 @@ RunPHATE.Seurat <- function(object, reduction = "pca", dims = NULL, features = N
   }
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < n_components) {
       stop(
         "Please provide as many or more features than n_components: ",
@@ -1448,7 +1448,7 @@ RunTriMap.Seurat <- function(object, reduction = "pca", dims = NULL, features =
   }
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < n_components) {
       stop(
         "Please provide as many or more features than n_components: ",
@@ -1570,7 +1570,7 @@ RunLargeVis.Seurat <- function(object, reduction = "pca", dims = NULL, features
   }
   if (!is.null(x = features)) {
     assay <- assay %||% DefaultAssay(object = object)
-    data.use <- as.matrix(x = t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
+    data.use <- as_matrix(t(x = GetAssayData(object = object, slot = slot, assay = assay)[features, , drop = FALSE]))
     if (ncol(x = data.use) < n_components) {
       stop(
         "Please provide as many or more features than n_components: ",
@@ -1824,7 +1824,7 @@ RunHarmony2.Seurat <- function(object, group.by.vars,
     ...
   )
 
-  harmonyEmbed <- t(as.matrix(harmonyObject$Z_corr))
+  harmonyEmbed <- t(as_matrix(harmonyObject$Z_corr))
   rownames(harmonyEmbed) <- row.names(data.use)
   colnames(harmonyEmbed) <- paste0(reduction.name, "_", seq_len(ncol(harmonyEmbed)))
 
diff --git a/R/utils.R b/R/utils.R
index 567b01f0..f0c043f2 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -816,24 +816,27 @@ unnest <- function(data, cols, keep_empty = FALSE) {
 }
 
 #' Attempts to turn a dgCMatrix into a dense matrix
-#' @param matrix A dgCMatrix
+#'
+#' @examples
+#' data("pancreas_sub")
+#' system.time(mat1 <- as.matrix(slot(pancreas_sub[["RNA"]], "counts")))
+#' system.time(mat2 <- as_matrix(slot(pancreas_sub[["RNA"]], "counts")))
+#' identical(mat1, mat2)
+#'
+#' @param x A matrix.
 #' @useDynLib SCP
+#' @importFrom Matrix as.matrix
 #' @export
-as_matrix <- function(matrix) {
+as_matrix <- function(x) {
   if (!inherits(matrix, "dgCMatrix")) {
-    stop("matrix is not a dgCMatrix.")
+    return(as.matrix(x))
+  } else {
+    row_pos <- x@i
+    col_pos <- findInterval(seq_along(x@x) - 1, x@p[-1])
+    out <- asMatrix(rp = row_pos, cp = col_pos, z = x@x, nrows = x@Dim[1], ncols = x@Dim[2])
+    attr(out, "dimnames") <- list(x@Dimnames[[1]], x@Dimnames[[2]])
+    return(out)
   }
-  row_pos <- matrix@i
-  col_pos <- findInterval(seq(matrix@x) - 1, matrix@p[-1])
-
-  out <- asMatrix(
-    rp = row_pos, cp = col_pos, z = matrix@x,
-    nrows = matrix@Dim[1], ncols = matrix@Dim[2]
-  )
-
-  row.names(out) <- matrix@Dimnames[[1]]
-  colnames(out) <- matrix@Dimnames[[2]]
-  return(out)
 }
 
 #' Capitalizes the characters
diff --git a/man/CellCorHeatmap.Rd b/man/CellCorHeatmap.Rd
index b07c141c..9c12ba94 100644
--- a/man/CellCorHeatmap.Rd
+++ b/man/CellCorHeatmap.Rd
@@ -59,13 +59,13 @@ CellCorHeatmap(
   query_cell_annotation = NULL,
   query_cell_annotation_palette = "Paired",
   query_cell_annotation_palcolor = NULL,
-  query_cell_annotation_params = if (flip) list(height = grid::unit(1, "cm")) else
-    list(width = grid::unit(1, "cm")),
+  query_cell_annotation_params = if (flip) list(height = grid::unit(20, "mm")) else
+    list(width = grid::unit(20, "mm")),
   ref_cell_annotation = NULL,
   ref_cell_annotation_palette = "Paired",
   ref_cell_annotation_palcolor = NULL,
-  ref_cell_annotation_params = if (flip) list(width = grid::unit(1, "cm")) else
-    list(height = grid::unit(1, "cm")),
+  ref_cell_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else
+    list(height = grid::unit(20, "mm")),
   use_raster = NULL,
   raster_device = "png",
   raster_by_magick = FALSE,
@@ -241,7 +241,7 @@ ht2 <- CellCorHeatmap(
   query_group = "SubCellType", ref_group = "celltype",
   query_cell_annotation = "Phase", query_cell_annotation_palette = "Set2",
   ref_cell_annotation = "tech", ref_cell_annotation_palette = "Set3",
-  width = 3, height = 2
+  width = 4, height = 4
 )
 ht2$plot
 
diff --git a/man/CellScoring.Rd b/man/CellScoring.Rd
index 5d5154de..bc53574b 100644
--- a/man/CellScoring.Rd
+++ b/man/CellScoring.Rd
@@ -86,7 +86,7 @@ data("pancreas_sub")
 ccgenes <- CC_GenePrefetch("Mus_musculus")
 pancreas_sub <- CellScoring(
   srt = pancreas_sub,
-  features = list(S = ccgenes$cc_S_genes, G2M = ccgenes$cc_G2M_genes),
+  features = list(S = ccgenes$S, G2M = ccgenes$G2M),
   method = "Seurat", name = "CC"
 )
 CellDimPlot(pancreas_sub, "CC_classification")
diff --git a/man/DynamicHeatmap.Rd b/man/DynamicHeatmap.Rd
index b929852b..c3a248c9 100644
--- a/man/DynamicHeatmap.Rd
+++ b/man/DynamicHeatmap.Rd
@@ -100,16 +100,18 @@ DynamicHeatmap(
   cell_annotation = NULL,
   cell_annotation_palette = "Paired",
   cell_annotation_palcolor = NULL,
-  cell_annotation_params = list(),
+  cell_annotation_params = if (flip) list(width = grid::unit(5, "mm")) else list(height =
+    grid::unit(5, "mm")),
   feature_annotation = NULL,
   feature_annotation_palette = "Dark2",
   feature_annotation_palcolor = NULL,
-  feature_annotation_params = list(),
+  feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else
+    list(width = grid::unit(5, "mm")),
   separate_annotation = NULL,
   separate_annotation_palette = "Paired",
   separate_annotation_palcolor = NULL,
-  separate_annotation_params = if (flip) list(width = grid::unit(2, "cm")) else
-    list(height = grid::unit(2, "cm")),
+  separate_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else
+    list(height = grid::unit(20, "mm")),
   reverse_ht = NULL,
   use_raster = NULL,
   raster_device = "png",
@@ -397,7 +399,7 @@ ht4 <- DynamicHeatmap(
   cell_annotation_palette = c("Paired", "simspec", "Purples"),
   separate_annotation = list("SubCellType", c("Nnat", "Irx1")),
   separate_annotation_palette = c("Paired", "Set1"),
-  separate_annotation_params = list(height = grid::unit(2, "cm")),
+  separate_annotation_params = list(height = grid::unit(20, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   pseudotime_label = 25,
@@ -417,7 +419,7 @@ ht5 <- DynamicHeatmap(
   cell_annotation_palette = c("Paired", "simspec", "Purples"),
   separate_annotation = list("SubCellType", c("Nnat", "Irx1")),
   separate_annotation_palette = c("Paired", "Set1"),
-  separate_annotation_params = list(width = grid::unit(2, "cm")),
+  separate_annotation_params = list(width = grid::unit(20, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   pseudotime_label = 25,
diff --git a/man/FeatureHeatmap.Rd b/man/FeatureHeatmap.Rd
index fa5d7063..5f03cab0 100644
--- a/man/FeatureHeatmap.Rd
+++ b/man/FeatureHeatmap.Rd
@@ -93,11 +93,13 @@ FeatureHeatmap(
   cell_annotation = NULL,
   cell_annotation_palette = "Paired",
   cell_annotation_palcolor = NULL,
-  cell_annotation_params = list(),
+  cell_annotation_params = if (flip) list(width = grid::unit(5, "mm")) else list(height =
+    grid::unit(5, "mm")),
   feature_annotation = NULL,
   feature_annotation_palette = "Dark2",
   feature_annotation_palcolor = NULL,
-  feature_annotation_params = list(),
+  feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else
+    list(width = grid::unit(5, "mm")),
   use_raster = NULL,
   raster_device = "png",
   raster_by_magick = FALSE,
diff --git a/man/FeatureStatPlot.Rd b/man/FeatureStatPlot.Rd
index fbb0a04d..7697c3f3 100644
--- a/man/FeatureStatPlot.Rd
+++ b/man/FeatureStatPlot.Rd
@@ -32,7 +32,7 @@ FeatureStatPlot(
   pt.color = "grey30",
   pt.size = NULL,
   pt.alpha = 1,
-  jitter.width = 0.5,
+  jitter.width = 0.4,
   jitter.height = 0.1,
   add_trend = FALSE,
   trend_color = "black",
@@ -266,6 +266,7 @@ FeatureStatPlot(pancreas_sub,
   group.by = "SubCellType", bg.by = "CellType", stack = TRUE, flip = TRUE
 ) \%>\% panel_fix_overall(width = 8, height = 5) # As the plot is created by combining, we can adjust the overall height and width directly.
 
+FeatureStatPlot(pancreas_sub, stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "group")
 FeatureStatPlot(pancreas_sub, stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "feature")
 FeatureStatPlot(pancreas_sub,
   stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType", plot.by = "feature",
@@ -286,7 +287,7 @@ FeatureStatPlot(pancreas_sub, stat.by = c(
 
 library(Matrix)
 data <- pancreas_sub@assays$RNA@data
-pancreas_sub@assays$RNA@scale.data <- as.matrix(data / rowMeans(data))
+pancreas_sub@assays$RNA@scale.data <- as_matrix(data / rowMeans(data))
 FeatureStatPlot(pancreas_sub,
   stat.by = c("Neurog3", "Rbp4", "Ins1"), group.by = "CellType",
   slot = "scale.data", ylab = "FoldChange", same.y.lims = TRUE, y.max = 4
diff --git a/man/FetchH5.Rd b/man/FetchH5.Rd
index 439970dc..9ee51669 100644
--- a/man/FetchH5.Rd
+++ b/man/FetchH5.Rd
@@ -43,7 +43,13 @@ This function fetches data from an hdf5 file. It can fetch gene expression data,
 data("pancreas_sub")
 pancreas_sub <- Standard_SCP(pancreas_sub)
 PrepareSCExplorer(pancreas_sub, base_dir = "./SCExplorer")
-srt <- FetchH5(DataFile = "./SCExplorer/Data.hdf5", MetaFile = "./SCExplorer/Meta.hdf5", features = c("Ins1", "Ghrl"), metanames = c("SubCellType", "Phase"), reduction = "UMAP")
+srt <- FetchH5(
+  DataFile = "./SCExplorer/Data.hdf5",
+  MetaFile = "./SCExplorer/Meta.hdf5",
+  features = c("Ins1", "Ghrl"),
+  metanames = c("SubCellType", "Phase"),
+  reduction = "UMAP"
+)
 CellDimPlot(srt, group.by = c("SubCellType", "Phase"), reduction = "UMAP")
 FeatureDimPlot(srt, features = c("Ins1", "Ghrl"), reduction = "UMAP")
 }
diff --git a/man/GeneConvert.Rd b/man/GeneConvert.Rd
index b9a4fec3..b18cb020 100644
--- a/man/GeneConvert.Rd
+++ b/man/GeneConvert.Rd
@@ -87,7 +87,7 @@ homologs_counts <- aggregate(
   by = list(res$geneID_expand[, "symbol"]), FUN = sum
 )
 rownames(homologs_counts) <- homologs_counts[, 1]
-homologs_counts <- as(as.matrix(homologs_counts[, -1]), "dgCMatrix")
+homologs_counts <- as(as_matrix(homologs_counts[, -1]), "dgCMatrix")
 homologs_counts
 
 }
diff --git a/man/GroupHeatmap.Rd b/man/GroupHeatmap.Rd
index d454313f..25e57f65 100644
--- a/man/GroupHeatmap.Rd
+++ b/man/GroupHeatmap.Rd
@@ -105,12 +105,13 @@ GroupHeatmap(
   cell_annotation = NULL,
   cell_annotation_palette = "Paired",
   cell_annotation_palcolor = NULL,
-  cell_annotation_params = if (flip) list(width = grid::unit(1, "cm")) else list(height =
-    grid::unit(1, "cm")),
+  cell_annotation_params = if (flip) list(width = grid::unit(20, "mm")) else list(height
+    = grid::unit(20, "mm")),
   feature_annotation = NULL,
   feature_annotation_palette = "Dark2",
   feature_annotation_palcolor = NULL,
-  feature_annotation_params = list(),
+  feature_annotation_params = if (flip) list(height = grid::unit(5, "mm")) else
+    list(width = grid::unit(5, "mm")),
   use_raster = NULL,
   raster_device = "png",
   raster_by_magick = FALSE,
@@ -373,8 +374,7 @@ ht1 <- GroupHeatmap(pancreas_sub,
     "Rbp4", "Pyy", # Endocrine
     "Ins1", "Gcg", "Sst", "Ghrl" # Beta, Alpha, Delta, Epsilon
   ),
-  group.by = c("CellType", "SubCellType"),
-  show_row_names = TRUE
+  group.by = c("CellType", "SubCellType")
 )
 ht1$plot
 panel_fix(ht1$plot, height = 4, width = 6, raster = TRUE, dpi = 50)
@@ -385,14 +385,12 @@ de_filter <- filter(pancreas_sub@tools$DEtest_CellType$AllMarkers_wilcox, p_val_
 ht2 <- GroupHeatmap(
   srt = pancreas_sub, features = de_filter$gene, group.by = "CellType",
   split.by = "Phase", cell_split_palette = "Dark2",
-  cluster_rows = TRUE, cluster_columns = TRUE,
-  nlabel = 10, show_row_names = FALSE
+  cluster_rows = TRUE, cluster_columns = TRUE
 )
 ht2$plot
 
 ht3 <- GroupHeatmap(
   srt = pancreas_sub, features = de_filter$gene, feature_split = de_filter$group1, group.by = "CellType",
-  nlabel = 20, show_row_names = FALSE,
   species = "Mus_musculus", db = "GO_BP", anno_terms = TRUE, anno_keys = TRUE, anno_features = TRUE
 )
 ht3$plot
@@ -407,10 +405,10 @@ ht4 <- GroupHeatmap(pancreas_sub,
   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
   heatmap_palette = "YlOrRd",
   cell_annotation = c("Phase", "G2M_score", "Neurod2"), cell_annotation_palette = c("Dark2", "Paired", "Paired"),
-  cell_annotation_params = list(height = grid::unit(0.5, "in")),
+  cell_annotation_params = list(height = grid::unit(20, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
-  add_dot = TRUE, add_bg = TRUE, show_row_names = TRUE
+  add_dot = TRUE, add_bg = TRUE, nlabel = 0, show_row_names = TRUE
 )
 ht4$plot
 
@@ -418,25 +416,25 @@ ht5 <- GroupHeatmap(pancreas_sub,
   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
   heatmap_palette = "YlOrRd",
   cell_annotation = c("Phase", "G2M_score", "Neurod2"), cell_annotation_palette = c("Dark2", "Paired", "Paired"),
-  cell_annotation_params = list(width = grid::unit(0.5, "in")),
+  cell_annotation_params = list(width = grid::unit(20, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   add_dot = TRUE, add_bg = TRUE,
-  flip = TRUE, column_title_rot = 45, show_column_names = TRUE
+  flip = TRUE, column_title_rot = 45, nlabel = 0, show_row_names = TRUE
 )
 ht5$plot
 
 ht6 <- GroupHeatmap(pancreas_sub,
   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
   add_violin = TRUE, cluster_rows = TRUE,
-  show_row_names = TRUE
+  nlabel = 0, show_row_names = TRUE
 )
 ht6$plot
 
 ht7 <- GroupHeatmap(pancreas_sub,
   features = de_top$gene, feature_split = de_top$group1, group.by = "CellType",
   add_violin = TRUE, fill.by = "expression", fill_palette = "Blues", cluster_rows = TRUE,
-  show_row_names = TRUE
+  nlabel = 0, show_row_names = TRUE
 )
 ht7$plot
 
@@ -444,7 +442,8 @@ ht8 <- GroupHeatmap(pancreas_sub,
   features = de_top$gene, group.by = "CellType", split.by = "Phase", n_split = 4,
   cluster_rows = TRUE, cluster_columns = TRUE, cluster_row_slices = TRUE, cluster_column_slices = TRUE,
   add_dot = TRUE, add_reticle = TRUE, heatmap_palette = "viridis",
-  show_row_names = TRUE, ht_params = list(row_gap = grid::unit(0, "mm"), row_names_gp = grid::gpar(fontsize = 10))
+  nlabel = 0, show_row_names = TRUE,
+  ht_params = list(row_gap = grid::unit(0, "mm"), row_names_gp = grid::gpar(fontsize = 10))
 )
 ht8$plot
 
diff --git a/man/RunSCExplorer.Rd b/man/RunSCExplorer.Rd
index 03ca1990..3af7b87a 100644
--- a/man/RunSCExplorer.Rd
+++ b/man/RunSCExplorer.Rd
@@ -15,14 +15,14 @@ RunSCExplorer(
   initial_feature = NULL,
   initial_assay = NULL,
   initial_slot = NULL,
-  initial_label = "No",
+  initial_label = FALSE,
   initial_cell_palette = "Paired",
   initial_feature_palette = "Spectral",
   initial_theme = "theme_scp",
   initial_size = 4,
   initial_ncol = 3,
-  initial_arrange = "Row",
-  initial_raster = "No",
+  initial_arrange = NULL,
+  initial_raster = NULL,
   session_workers = 2,
   plotting_workers = 8,
   create_script = TRUE,
@@ -52,7 +52,7 @@ RunSCExplorer(
 
 \item{initial_slot}{A string. The initial slot to be loaded into the app. Default is NULL.}
 
-\item{initial_label}{A string. Whether to add labels in the initial plot. Default is "No".}
+\item{initial_label}{A string. Whether to add labels in the initial plot. Default is FALSE.}
 
 \item{initial_cell_palette}{A string. The initial color palette for cells. Default is "Paired".}
 
@@ -64,7 +64,9 @@ RunSCExplorer(
 
 \item{initial_ncol}{A numeric. The initial number of columns for arranging plots. Default is 3.}
 
-\item{initial_arrange}{A string. The initial arrangement of plots. Default is "Row".}
+\item{initial_arrange}{A logical. Whether to use "Row" as the initial arrangement. Default is TRUE.}
+
+\item{initial_raster}{A logical. Whether to perform rasterization in the initial plot. By default, it is set to automatic, meaning it will be TRUE if the number of cells in the initial datasets exceeds 100,000.}
 
 \item{session_workers}{A numeric. The number of workers for concurrent execution in an asynchronous programming session. Default is 2.}
 
diff --git a/man/as_matrix.Rd b/man/as_matrix.Rd
index 1687aedd..c284c0a9 100644
--- a/man/as_matrix.Rd
+++ b/man/as_matrix.Rd
@@ -4,11 +4,18 @@
 \alias{as_matrix}
 \title{Attempts to turn a dgCMatrix into a dense matrix}
 \usage{
-as_matrix(matrix)
+as_matrix(x)
 }
 \arguments{
-\item{matrix}{A dgCMatrix}
+\item{x}{A matrix.}
 }
 \description{
 Attempts to turn a dgCMatrix into a dense matrix
 }
+\examples{
+data("pancreas_sub")
+system.time(mat1 <- as.matrix(slot(pancreas_sub[["RNA"]], "counts")))
+system.time(mat2 <- as_matrix(slot(pancreas_sub[["RNA"]], "counts")))
+identical(mat1, mat2)
+
+}
diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp
index 94c018ca..ec7932f3 100644
--- a/src/RcppExports.cpp
+++ b/src/RcppExports.cpp
@@ -11,7 +11,7 @@ Rcpp::Rostream<false>& Rcpp::Rcerr = Rcpp::Rcpp_cerr_get();
 #endif
 
 // asMatrix
-IntegerMatrix asMatrix(NumericVector rp, NumericVector cp, NumericVector z, int nrows, int ncols);
+NumericMatrix asMatrix(NumericVector rp, NumericVector cp, NumericVector z, int nrows, int ncols);
 RcppExport SEXP _SCP_asMatrix(SEXP rpSEXP, SEXP cpSEXP, SEXP zSEXP, SEXP nrowsSEXP, SEXP ncolsSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
diff --git a/src/asMatrix.cpp b/src/asMatrix.cpp
index 5f9b2ca0..0897a1ba 100644
--- a/src/asMatrix.cpp
+++ b/src/asMatrix.cpp
@@ -1,21 +1,20 @@
-#include <Rcpp.h>
-using namespace Rcpp;
+#include <Rcpp.h>    
+using namespace Rcpp;    
 
-
-// [[Rcpp::export]]
-IntegerMatrix asMatrix(NumericVector rp,
+// [[Rcpp::export]]    
+NumericMatrix asMatrix(NumericVector rp,
                        NumericVector cp,
                        NumericVector z,
                        int nrows,
                        int ncols){
   
-  int k = z.size() ;
+  int k = z.size() ;    
   
-  IntegerMatrix  mat(nrows, ncols);
+  NumericMatrix mat(nrows, ncols);    
   
-  for (int i = 0; i < k; i++){
-    mat(rp[i],cp[i]) = z[i];
-  }
+  for (int i = 0; i < k; i++){    
+    mat(rp[i],cp[i]) = z[i];    
+  }    
   
-  return mat;
-}
\ No newline at end of file
+  return mat;    
+}

From f0a0b4e7a9039a2c0534537b92a0e1c34daa1346 Mon Sep 17 00:00:00 2001
From: zhanghao-njmu <542370159@qq.com>
Date: Tue, 14 Nov 2023 15:13:20 +0800
Subject: [PATCH 4/4] Increment version number to 0.5.5

---
 DESCRIPTION | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 55efbad8..d22293d1 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: SCP
 Type: Package
 Title: Single Cell Pipeline
-Version: 0.5.4
+Version: 0.5.5
 Author: Hao Zhang
 Maintainer: Hao Zhang <haozhang@njmu.edu.cn>
 Description: An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.