From 29371be8e15a4975892879932fe6a567166ba0e3 Mon Sep 17 00:00:00 2001
From: zhanghao-njmu <542370159@qq.com>
Date: Sun, 19 Nov 2023 23:21:39 +0800
Subject: [PATCH] The calculation strategy for p.adjust in RunDEtest has been
 modified so that p.adjust is conducted within each group of comparisons
 instead of globally.

---
 R/SCP-analysis.R       | 24 +++++++---------
 R/SCP-app.R            |  8 ++++--
 R/SCP-cellqc.R         | 17 ++++++-----
 R/SCP-plot.R           | 65 ++++++++++++++++++++++++------------------
 R/Seurat-function.R    | 18 ++++++------
 man/CellCorHeatmap.Rd  |  8 +++---
 man/DynamicHeatmap.Rd  |  8 +++---
 man/FeatureStatPlot.Rd |  8 ++++++
 man/GroupHeatmap.Rd    |  8 +++---
 man/RunCellQC.Rd       | 10 +++----
 man/RunUMAP2.Rd        |  2 ++
 11 files changed, 99 insertions(+), 77 deletions(-)

diff --git a/R/SCP-analysis.R b/R/SCP-analysis.R
index a8b3df7e..b0c1bc87 100644
--- a/R/SCP-analysis.R
+++ b/R/SCP-analysis.R
@@ -1925,6 +1925,9 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
             markers[, "gene"] <- rownames(markers)
             markers[, "group1"] <- as.character(group)
             markers[, "group2"] <- "others"
+            if ("p_val" %in% colnames(markers)) {
+              markers[, "p_val_adj"] <- p.adjust(markers[, "p_val"], method = p.adjust.method)
+            }
             return(markers)
           } else {
             return(NULL)
@@ -1935,9 +1938,6 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
       if (!is.null(AllMarkers) && nrow(AllMarkers) > 0) {
         rownames(AllMarkers) <- NULL
         AllMarkers[, "group1"] <- factor(AllMarkers[, "group1"], levels = levels(cell_group))
-        if ("p_val" %in% colnames(AllMarkers)) {
-          AllMarkers[, "p_val_adj"] <- p.adjust(AllMarkers[, "p_val"], method = p.adjust.method)
-        }
         AllMarkers[, "test_group_number"] <- as.integer(table(AllMarkers[["gene"]])[AllMarkers[, "gene"]])
         AllMarkersMatrix <- as.data.frame.matrix(table(AllMarkers[, c("gene", "group1")]))
         AllMarkers[, "test_group"] <- apply(AllMarkersMatrix, 1, function(x) {
@@ -1965,6 +1965,9 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
             markers[, "gene"] <- rownames(markers)
             markers[, "group1"] <- as.character(pair[i, 1])
             markers[, "group2"] <- as.character(pair[i, 2])
+            if ("p_val" %in% colnames(markers)) {
+              markers[, "p_val_adj"] <- p.adjust(markers[, "p_val"], method = p.adjust.method)
+            }
             return(markers)
           } else {
             return(NULL)
@@ -1975,9 +1978,6 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
       if (!is.null(PairedMarkers) && nrow(PairedMarkers) > 0) {
         rownames(PairedMarkers) <- NULL
         PairedMarkers[, "group1"] <- factor(PairedMarkers[, "group1"], levels = levels(cell_group))
-        if ("p_val" %in% colnames(PairedMarkers)) {
-          PairedMarkers[, "p_val_adj"] <- p.adjust(PairedMarkers[, "p_val"], method = p.adjust.method)
-        }
         PairedMarkers[, "test_group_number"] <- as.integer(table(PairedMarkers[["gene"]])[PairedMarkers[, "gene"]])
         PairedMarkersMatrix <- as.data.frame.matrix(table(PairedMarkers[, c("gene", "group1")]))
         PairedMarkers[, "test_group"] <- apply(PairedMarkersMatrix, 1, function(x) {
@@ -2011,19 +2011,19 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
             markers[, "gene"] <- rownames(markers)
             markers[, "group1"] <- as.character(group)
             markers[, "group2"] <- "others"
+            if ("p_val" %in% colnames(markers)) {
+              markers[, "p_val_adj"] <- p.adjust(markers[, "p_val"], method = p.adjust.method)
+            }
             return(markers)
           } else {
             return(NULL)
           }
         }
       }, BPPARAM = BPPARAM)
-      ConservedMarkers <- do.call(rbind.data.frame, lapply(ConservedMarkers, function(x) x[, c("avg_log2FC", "pct.1", "pct.2", "max_pval", "p_val", "gene", "group1", "group2")]))
+      ConservedMarkers <- do.call(rbind.data.frame, lapply(ConservedMarkers, function(x) x[, c("avg_log2FC", "pct.1", "pct.2", "max_pval", "p_val", "p_val_adj", "gene", "group1", "group2")]))
       if (!is.null(ConservedMarkers) && nrow(ConservedMarkers) > 0) {
         rownames(ConservedMarkers) <- NULL
         ConservedMarkers[, "group1"] <- factor(ConservedMarkers[, "group1"], levels = levels(cell_group))
-        if ("p_val" %in% colnames(ConservedMarkers)) {
-          ConservedMarkers[, "p_val_adj"] <- p.adjust(ConservedMarkers[, "p_val"], method = p.adjust.method)
-        }
         ConservedMarkers[, "test_group_number"] <- as.integer(table(ConservedMarkers[["gene"]])[ConservedMarkers[, "gene"]])
         ConservedMarkersMatrix <- as.data.frame.matrix(table(ConservedMarkers[, c("gene", "group1")]))
         ConservedMarkers[, "test_group"] <- apply(ConservedMarkersMatrix, 1, function(x) {
@@ -2085,9 +2085,6 @@ RunDEtest <- function(srt, group_by = NULL, group1 = NULL, group2 = NULL, cells1
       if (!is.null(DisturbedMarkers) && nrow(DisturbedMarkers) > 0) {
         rownames(DisturbedMarkers) <- NULL
         DisturbedMarkers[, "group1"] <- factor(DisturbedMarkers[, "group1"], levels = levels(cell_group))
-        if ("p_val" %in% colnames(DisturbedMarkers)) {
-          DisturbedMarkers[, "p_val_adj"] <- p.adjust(DisturbedMarkers[, "p_val"], method = p.adjust.method)
-        }
         DisturbedMarkers[, "test_group_number"] <- as.integer(table(unique(DisturbedMarkers[, c("gene", "group1")])[["gene"]])[DisturbedMarkers[, "gene"]])
         DisturbedMarkersMatrix <- as.data.frame.matrix(table(DisturbedMarkers[, c("gene", "group1")]))
         DisturbedMarkers[, "test_group"] <- apply(DisturbedMarkersMatrix, 1, function(x) {
@@ -5398,6 +5395,7 @@ srt_to_adata <- function(srt, features = NULL,
     var[["highly_variable"]] <- features %in% VariableFeatures(srt, assay = assay_X)
   }
 
+  # X <- t(as_matrix(slot(srt@assays[[assay_X]], slot_X)[features, , drop = FALSE]))
   X <- t(GetAssayData(srt, assay = assay_X, slot = slot_X)[features, , drop = FALSE])
   adata <- sc$AnnData(
     X = np_array(X, dtype = np$float32),
diff --git a/R/SCP-app.R b/R/SCP-app.R
index d2003679..af18df30 100644
--- a/R/SCP-app.R
+++ b/R/SCP-app.R
@@ -145,7 +145,7 @@ CreateMetaFile <- function(srt, MetaFile, name = NULL, write_tools = FALSE, writ
       meta_asfeatures <- c(meta_asfeatures, var)
     } 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)
+        warning("The number of categories in ", var, " is greater than ", ignore_nlevel, ". It will be ignored.", immediate. = TRUE)
       } else {
         meta_asgroups <- c(meta_asgroups, var)
       }
@@ -156,7 +156,11 @@ CreateMetaFile <- function(srt, MetaFile, name = NULL, write_tools = FALSE, writ
     if (paste0(name, "/metadata/", var) %in% paste0(h5ls(MetaFile)$group, "/", h5ls(MetaFile)$name)) {
       message("Group ", paste0(name, "/metadata/", var), " already exists in the ", MetaFile)
     } else {
-      h5write(obj = meta, file = MetaFile, name = paste0(name, "/metadata/", var), write.attributes = write.attributes, level = compression_level)
+      if (all(is.na(meta))) {
+        warning("All of values in ", var, " is NA. It will be ignored.", immediate. = TRUE)
+      } else {
+        h5write(obj = meta, file = MetaFile, name = paste0(name, "/metadata/", var), write.attributes = write.attributes, level = compression_level)
+      }
     }
   }
 
diff --git a/R/SCP-cellqc.R b/R/SCP-cellqc.R
index c716d3b8..7ceb2b6b 100644
--- a/R/SCP-cellqc.R
+++ b/R/SCP-cellqc.R
@@ -259,10 +259,10 @@ isOutlier <- function(x, nmads = 2.5, constant = 1.4826, type = c("both", "lower
 #'
 #' @inheritParams RunDoubletCalling
 #' @param split.by Name of the sample variable to split the Seurat object. Default is NULL.
+#' @param return_filtered Logical indicating whether to return a cell-filtered Seurat object. Default is FALSE.
 #' @param qc_metrics A character vector specifying the quality control metrics to be applied. Default is
 #'   `c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio", "species")`.
-#' @param return_filtered Logical indicating whether to return a cell-filtered Seurat object. Default is FALSE.
-#' @param outlier_cutoff A character vector specifying the outlier cutoff values. Default is
+#' @param outlier_threshold A character vector specifying the outlier threshold. Default is
 #'   `c("log10_nCount:lower:2.5", "log10_nCount:higher:5", "log10_nFeature:lower:2.5", "log10_nFeature:higher:5", "featurecount_dist:lower:2.5")`. See \link[scuttle]{isOutlier}.
 #' @param db_coefficient The coefficient used to calculate the doublet rate. Default is 0.01. Doublet rate is calculated as`ncol(srt) / 1000 * db_coefficient`
 #' @param outlier_n Minimum number of outlier metrics that meet the conditions for determining outlier cells. Default is 1.
@@ -311,11 +311,10 @@ isOutlier <- function(x, nmads = 2.5, constant = 1.4826, type = c("both", "lower
 #' @importFrom Matrix colSums t
 #' @export
 #'
-RunCellQC <- function(srt, assay = "RNA", split.by = NULL,
+RunCellQC <- function(srt, assay = "RNA", split.by = NULL, return_filtered = FALSE,
                       qc_metrics = c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio", "species"),
-                      return_filtered = FALSE,
                       db_method = "scDblFinder", db_rate = NULL, db_coefficient = 0.01,
-                      outlier_cutoff = c(
+                      outlier_threshold = c(
                         "log10_nCount:lower:2.5",
                         "log10_nCount:higher:5",
                         "log10_nFeature:lower:2.5",
@@ -344,7 +343,7 @@ RunCellQC <- function(srt, assay = "RNA", split.by = NULL,
   }
   status <- check_DataType(srt, slot = "counts", assay = assay)
   if (status != "raw_counts") {
-    warning("Data type is not raw counts!")
+    warning("Data type is not raw counts!", immediate. = TRUE)
   }
   if (!paste0("nCount_", assay) %in% colnames(srt@meta.data)) {
     srt@meta.data[[paste0("nCount_", assay)]] <- colSums(srt[[assay]]@counts)
@@ -429,15 +428,15 @@ RunCellQC <- function(srt, assay = "RNA", split.by = NULL,
           #   theme(panel.background = element_rect(fill = "grey"))
           # nrow(lower_df)
 
-          var <- sapply(strsplit(outlier_cutoff, ":"), function(x) x[[1]])
+          var <- sapply(strsplit(outlier_threshold, ":"), function(x) x[[1]])
           var_valid <- var %in% colnames(srt@meta.data) | sapply(var, FUN = function(x) exists(x, where = environment()))
           if (any(!var_valid)) {
             stop("Variable ", paste0(names(var_valid)[!var_valid], collapse = ","), " is not found in the srt object.")
           }
-          outlier <- lapply(strsplit(outlier_cutoff, ":"), function(m) {
+          outlier <- lapply(strsplit(outlier_threshold, ":"), function(m) {
             colnames(srt)[isOutlier(get(m[1]), nmads = as.numeric(m[3]), type = m[2])]
           })
-          names(outlier) <- outlier_cutoff
+          names(outlier) <- outlier_threshold
           # print(unlist(lapply(outlier, length)))
           outlier_tb <- table(unlist(outlier))
           outlier_qc <- c(outlier_qc, names(outlier_tb)[outlier_tb >= outlier_n])
diff --git a/R/SCP-plot.R b/R/SCP-plot.R
index 602d2a61..4d003fc2 100644
--- a/R/SCP-plot.R
+++ b/R/SCP-plot.R
@@ -1590,11 +1590,11 @@ CellDimPlot <- function(srt, group.by, reduction = NULL, dims = c(1, 2), split.b
       p <- p + scattermore::geom_scattermore(
         data = dat[is.na(dat[, "group.by"]), , drop = FALSE],
         mapping = aes(x = .data[["x"]], y = .data[["y"]]), color = bg_color,
-        pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+        pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
       ) + scattermore::geom_scattermore(
         data = dat[!is.na(dat[, "group.by"]), , drop = FALSE],
         mapping = aes(x = .data[["x"]], y = .data[["y"]], color = .data[["group.by"]]),
-        pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+        pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
       )
     } else if (isTRUE(hex)) {
       check_R("hexbin")
@@ -2325,12 +2325,12 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
         p <- p + scattermore::geom_scattermore(
           data = dat[dat[, "color_blend"] == bg_color, , drop = FALSE],
           mapping = aes(x = .data[["x"]], y = .data[["y"]], color = .data[["color_blend"]]),
-          pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+          pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
         ) +
           scattermore::geom_scattermore(
             data = dat[dat[, "color_blend"] != bg_color, , drop = FALSE],
             mapping = aes(x = .data[["x"]], y = .data[["y"]], color = .data[["color_blend"]]),
-            pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+            pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
           ) +
           scale_color_identity() +
           new_scale_color()
@@ -2599,12 +2599,12 @@ FeatureDimPlot <- function(srt, features, reduction = NULL, dims = c(1, 2), spli
         p <- p + scattermore::geom_scattermore(
           data = dat[is.na(dat[, "value"]), , drop = FALSE],
           mapping = aes(x = .data[["x"]], y = .data[["y"]], color = .data[["value"]]),
-          pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+          pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
         ) +
           scattermore::geom_scattermore(
             data = dat[!is.na(dat[, "value"]), , drop = FALSE],
             mapping = aes(x = .data[["x"]], y = .data[["y"]], color = .data[["value"]]),
-            pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+            pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
           )
       } else if (isTRUE(hex)) {
         check_R("hexbin")
@@ -3399,6 +3399,8 @@ FeatureDimPlot3D <- function(srt, features, reduction = NULL, dims = c(1, 2, 3),
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_box = TRUE)
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_point = TRUE)
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_trend = TRUE)
+#' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_stat = "mean")
+#' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_line = 0.2, line_type = 2)
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase")
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase", add_box = TRUE, add_trend = TRUE)
 #' FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase", comparisons = TRUE)
@@ -3471,7 +3473,8 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
                             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 = 0.4, 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,
+                            add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1, stat_stroke = 1, stat_shape = 25,
+                            add_line = NULL, line_color = "red", line_size = 1, line_type = 1,
                             cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
                             calculate_coexp = FALSE,
                             same.y.lims = FALSE, y.min = NULL, y.max = NULL, y.trans = "identity", y.nbreaks = 5,
@@ -3524,7 +3527,8 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
           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, 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,
+          add_stat = add_stat, stat_color = stat_color, stat_size = stat_size, stat_stroke = stat_stroke, stat_shape = stat_shape,
+          add_line = add_line, line_color = line_color, line_size = line_size, line_type = line_type,
           cells.highlight = cells.highlight, cols.highlight = cols.highlight, sizes.highlight = sizes.highlight, alpha.highlight = alpha.highlight,
           calculate_coexp = calculate_coexp,
           same.y.lims = same.y.lims, y.min = y.min, y.max = y.max, y.trans = y.trans, y.nbreaks = y.nbreaks,
@@ -3551,7 +3555,8 @@ FeatureStatPlot <- function(srt, stat.by, group.by = NULL, split.by = NULL, bg.b
       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, 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,
+      add_stat = add_stat, stat_color = stat_color, stat_size = stat_size, stat_stroke = stat_stroke, stat_shape = stat_shape,
+      add_line = add_line, line_color = line_color, line_size = line_size, line_type = line_type,
       cells.highlight = cells.highlight, cols.highlight = cols.highlight, sizes.highlight = sizes.highlight, alpha.highlight = alpha.highlight,
       calculate_coexp = calculate_coexp,
       same.y.lims = same.y.lims, y.min = y.min, y.max = y.max, y.trans = y.trans, y.nbreaks = y.nbreaks,
@@ -3667,7 +3672,8 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
                                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 = 0.4, 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,
+                               add_stat = c("none", "mean", "median"), stat_color = "black", stat_size = 1, stat_stroke = 1, stat_shape = 25,
+                               add_line = NULL, line_color = "red", line_size = 1, line_type = 1,
                                cells.highlight = NULL, cols.highlight = "red", sizes.highlight = 1, alpha.highlight = 1,
                                calculate_coexp = FALSE,
                                same.y.lims = FALSE, y.min = NULL, y.max = NULL, y.trans = "identity", y.nbreaks = 5,
@@ -3686,6 +3692,9 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
   fill.by <- match.arg(fill.by)
   sig_label <- match.arg(sig_label)
   add_stat <- match.arg(add_stat)
+  if (!is.null(add_line)) {
+    stopifnot(is.numeric(add_line))
+  }
 
   if (missing(exp.data)) {
     exp.data <- matrix(0, nrow = 1, ncol = nrow(meta.data), dimnames = list("", rownames(meta.data)))
@@ -4245,10 +4254,16 @@ ExpressionStatPlot <- function(exp.data, meta.data, stat.by, group.by = NULL, sp
     }
     if (add_stat != "none") {
       p <- p + stat_summary(
-        fun = add_stat, geom = "point", mapping = aes(group = .data[["split.by"]], shape = 95),
-        position = position_dodge(width = 0.9), color = stat_color, fill = "white", size = stat_size, stroke = 10,
+        fun = add_stat, geom = "point", mapping = aes(group = .data[["split.by"]], shape = stat_shape),
+        position = position_dodge(width = 0.9), color = stat_color, fill = stat_color, size = stat_size, stroke = stat_stroke,
       ) + scale_shape_identity()
     }
+    if (!is.null(add_line)) {
+      p <- p + geom_hline(
+        yintercept = add_line,
+        color = line_color, linetype = line_type, linewidth = line_size
+      )
+    }
 
     if (nrow(dat) == 0) {
       p <- p + facet_null()
@@ -5356,7 +5371,7 @@ FeatureCorPlot <- function(srt, features, group.by = NULL, split.by = NULL, cell
         if (isTRUE(raster)) {
           p <- p + scattermore::geom_scattermore(
             mapping = aes(x = .data[[f1]], y = .data[[f2]], color = .data[[group.by]]),
-            pointsize = floor(pt.size), alpha = pt.alpha, pixels = raster.dpi
+            pointsize = ceiling(pt.size), alpha = pt.alpha, pixels = raster.dpi
           )
         } else {
           p <- p + geom_point(aes(x = .data[[f1]], y = .data[[f2]], color = .data[[group.by]]),
@@ -7786,7 +7801,7 @@ 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(20, "mm")),
+#'   cell_annotation_params = list(height = grid::unit(10, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   add_dot = TRUE, add_bg = TRUE, nlabel = 0, show_row_names = TRUE
@@ -7797,7 +7812,7 @@ 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(20, "mm")),
+#'   cell_annotation_params = list(width = grid::unit(10, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   add_dot = TRUE, add_bg = TRUE,
@@ -7862,7 +7877,7 @@ 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(20, "mm")) else list(height = grid::unit(20, "mm")),
+                         cell_annotation = NULL, cell_annotation_palette = "Paired", cell_annotation_palcolor = NULL, cell_annotation_params = if (flip) list(width = grid::unit(10, "mm")) else list(height = grid::unit(10, "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()) {
@@ -8878,9 +8893,7 @@ GroupHeatmap <- function(srt, features = NULL, group.by = NULL, split.by = NULL,
   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
@@ -9822,9 +9835,7 @@ FeatureHeatmap <- function(srt, features = NULL, cells = NULL, group.by = NULL,
   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
@@ -10064,8 +10075,8 @@ 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(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")),
+                           query_cell_annotation = NULL, query_cell_annotation_palette = "Paired", query_cell_annotation_palcolor = NULL, query_cell_annotation_params = if (flip) list(height = grid::unit(10, "mm")) else list(width = grid::unit(10, "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(10, "mm")) else list(height = grid::unit(10, "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)
@@ -10892,7 +10903,7 @@ 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(20, "mm")),
+#'   separate_annotation_params = list(height = grid::unit(10, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   pseudotime_label = 25,
@@ -10912,7 +10923,7 @@ 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(20, "mm")),
+#'   separate_annotation_params = list(width = grid::unit(10, "mm")),
 #'   feature_annotation = c("TF", "CSPA"),
 #'   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
 #'   pseudotime_label = 25,
@@ -10969,7 +10980,7 @@ DynamicHeatmap <- function(srt, lineages, features = NULL, use_fitted = FALSE, b
                            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(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")),
+                           separate_annotation = NULL, separate_annotation_palette = "Paired", separate_annotation_palcolor = NULL, separate_annotation_params = if (flip) list(width = grid::unit(10, "mm")) else list(height = grid::unit(10, "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)
diff --git a/R/Seurat-function.R b/R/Seurat-function.R
index 460b7788..b984d1f9 100644
--- a/R/Seurat-function.R
+++ b/R/Seurat-function.R
@@ -587,7 +587,7 @@ RunUMAP2 <- function(object, ...) {
 RunUMAP2.Seurat <- function(object,
                             reduction = "pca", dims = NULL, features = NULL, neighbor = NULL, graph = NULL,
                             assay = NULL, slot = "data",
-                            umap.method = "uwot", reduction.model = NULL,
+                            umap.method = "uwot", reduction.model = NULL, n_threads = NULL,
                             return.model = FALSE, n.neighbors = 30L, n.components = 2L,
                             metric = "cosine", n.epochs = 200L, spread = 1, min.dist = 0.3,
                             set.op.mix.ratio = 1, local.connectivity = 1L, negative.sample.rate = 5L,
@@ -667,7 +667,7 @@ RunUMAP2.Seurat <- function(object,
 #' @importFrom Matrix sparseMatrix
 #' @export
 RunUMAP2.default <- function(object, assay = NULL,
-                             umap.method = "uwot", reduction.model = NULL,
+                             umap.method = "uwot", reduction.model = NULL, n_threads = NULL,
                              return.model = FALSE, n.neighbors = 30L, n.components = 2L,
                              metric = "cosine", n.epochs = 200L, spread = 1, min.dist = 0.3,
                              set.op.mix.ratio = 1, local.connectivity = 1L, negative.sample.rate = 5L,
@@ -879,7 +879,7 @@ RunUMAP2.default <- function(object, assay = NULL,
   if (umap.method == "uwot") {
     if (inherits(x = object, what = "dist")) {
       embeddings <- uwot::umap(
-        X = object, n_neighbors = n.neighbors, n_threads = 1, n_components = n.components,
+        X = object, n_neighbors = n.neighbors, n_threads = n_threads, n_components = n.components,
         metric = metric, n_epochs = n.epochs, learning_rate = learning.rate,
         min_dist = min.dist, spread = spread, set_op_mix_ratio = set.op.mix.ratio,
         local_connectivity = local.connectivity, repulsion_strength = repulsion.strength,
@@ -904,7 +904,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       # object <- srt@neighbors$Seurat.nn
       # object <- list(idx = Indices(object), dist = Distances(object))
       out <- uwot::umap(
-        X = NULL, nn_method = object, n_threads = 1, n_components = n.components,
+        X = NULL, nn_method = object, n_threads = n_threads, n_components = n.components,
         metric = metric, n_epochs = n.epochs, learning_rate = learning.rate,
         min_dist = min.dist, spread = spread, set_op_mix_ratio = set.op.mix.ratio,
         local_connectivity = local.connectivity, repulsion_strength = repulsion.strength,
@@ -962,7 +962,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       # idx <- t(as_matrix(apply(object, 2, function(x) order(x, decreasing = TRUE)[1:n.neighbors])))
       # connectivity <- t(as_matrix(apply(object, 2, function(x) x[order(x, decreasing = TRUE)[1:n.neighbors]])))
       out <- uwot::umap(
-        X = NULL, nn_method = nn, n_threads = 1, n_components = n.components,
+        X = NULL, nn_method = nn, n_threads = n_threads, n_components = n.components,
         metric = metric, n_epochs = n.epochs, learning_rate = learning.rate,
         min_dist = min.dist, spread = spread, set_op_mix_ratio = set.op.mix.ratio,
         local_connectivity = local.connectivity, repulsion_strength = repulsion.strength,
@@ -1004,7 +1004,7 @@ RunUMAP2.default <- function(object, assay = NULL,
     if (inherits(x = object, what = "matrix") || inherits(x = object, what = "Matrix")) {
       # object <- srt@reductions$Seuratpca@cell.embeddings
       out <- uwot::umap(
-        X = object, n_neighbors = n.neighbors, n_threads = 1, n_components = n.components,
+        X = object, n_neighbors = n.neighbors, n_threads = n_threads, n_components = n.components,
         metric = metric, n_epochs = n.epochs, learning_rate = learning.rate,
         min_dist = min.dist, spread = spread, set_op_mix_ratio = set.op.mix.ratio,
         local_connectivity = local.connectivity, repulsion_strength = repulsion.strength,
@@ -1067,7 +1067,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       }
       embeddings <- uwot::umap_transform(
         X = NULL, nn_method = object, model = model, n_epochs = n.epochs,
-        n_threads = 1, verbose = verbose
+        n_threads = n_threads, verbose = verbose
       )
       rownames(x = embeddings) <- row.names(object[["idx"]])
       colnames(x = embeddings) <- paste0(reduction.key, 1:n.components)
@@ -1088,7 +1088,7 @@ RunUMAP2.default <- function(object, assay = NULL,
       }
       embeddings <- uwot::umap_transform(
         X = NULL, nn_method = object, model = model, n_epochs = n.epochs,
-        n_threads = 1, verbose = verbose
+        n_threads = n_threads, verbose = verbose
       )
       rownames(x = embeddings) <- row.names(object[["idx"]])
       colnames(x = embeddings) <- paste0(reduction.key, 1:n.components)
@@ -1103,7 +1103,7 @@ RunUMAP2.default <- function(object, assay = NULL,
     if (inherits(x = object, what = "matrix") || inherits(x = object, what = "Matrix")) {
       embeddings <- uwot::umap_transform(
         X = object, model = model, n_epochs = n.epochs,
-        n_threads = 1, verbose = verbose
+        n_threads = n_threads, verbose = verbose
       )
       rownames(x = embeddings) <- row.names(object)
       colnames(x = embeddings) <- paste0(reduction.key, 1:n.components)
diff --git a/man/CellCorHeatmap.Rd b/man/CellCorHeatmap.Rd
index 9c12ba94..85ca5dbd 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(20, "mm")) else
-    list(width = grid::unit(20, "mm")),
+  query_cell_annotation_params = if (flip) list(height = grid::unit(10, "mm")) else
+    list(width = grid::unit(10, "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")),
+  ref_cell_annotation_params = if (flip) list(width = grid::unit(10, "mm")) else
+    list(height = grid::unit(10, "mm")),
   use_raster = NULL,
   raster_device = "png",
   raster_by_magick = FALSE,
diff --git a/man/DynamicHeatmap.Rd b/man/DynamicHeatmap.Rd
index c3a248c9..57410020 100644
--- a/man/DynamicHeatmap.Rd
+++ b/man/DynamicHeatmap.Rd
@@ -110,8 +110,8 @@ DynamicHeatmap(
   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")),
+  separate_annotation_params = if (flip) list(width = grid::unit(10, "mm")) else
+    list(height = grid::unit(10, "mm")),
   reverse_ht = NULL,
   use_raster = NULL,
   raster_device = "png",
@@ -399,7 +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(20, "mm")),
+  separate_annotation_params = list(height = grid::unit(10, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   pseudotime_label = 25,
@@ -419,7 +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(20, "mm")),
+  separate_annotation_params = list(width = grid::unit(10, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   pseudotime_label = 25,
diff --git a/man/FeatureStatPlot.Rd b/man/FeatureStatPlot.Rd
index 7697c3f3..58bc795e 100644
--- a/man/FeatureStatPlot.Rd
+++ b/man/FeatureStatPlot.Rd
@@ -41,6 +41,12 @@ FeatureStatPlot(
   add_stat = c("none", "mean", "median"),
   stat_color = "black",
   stat_size = 1,
+  stat_stroke = 1,
+  stat_shape = 25,
+  add_line = NULL,
+  line_color = "red",
+  line_size = 1,
+  line_type = 1,
   cells.highlight = NULL,
   cols.highlight = "red",
   sizes.highlight = 1,
@@ -235,6 +241,8 @@ FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCe
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_box = TRUE)
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_point = TRUE)
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_trend = TRUE)
+FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_stat = "mean")
+FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", add_line = 0.2, line_type = 2)
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase")
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase", add_box = TRUE, add_trend = TRUE)
 FeatureStatPlot(pancreas_sub, stat.by = c("G2M_score", "Fev"), group.by = "SubCellType", split.by = "Phase", comparisons = TRUE)
diff --git a/man/GroupHeatmap.Rd b/man/GroupHeatmap.Rd
index 25e57f65..93586a4d 100644
--- a/man/GroupHeatmap.Rd
+++ b/man/GroupHeatmap.Rd
@@ -105,8 +105,8 @@ GroupHeatmap(
   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")),
+  cell_annotation_params = if (flip) list(width = grid::unit(10, "mm")) else list(height
+    = grid::unit(10, "mm")),
   feature_annotation = NULL,
   feature_annotation_palette = "Dark2",
   feature_annotation_palcolor = NULL,
@@ -405,7 +405,7 @@ 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(20, "mm")),
+  cell_annotation_params = list(height = grid::unit(10, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   add_dot = TRUE, add_bg = TRUE, nlabel = 0, show_row_names = TRUE
@@ -416,7 +416,7 @@ 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(20, "mm")),
+  cell_annotation_params = list(width = grid::unit(10, "mm")),
   feature_annotation = c("TF", "CSPA"),
   feature_annotation_palcolor = list(c("gold", "steelblue"), c("forestgreen")),
   add_dot = TRUE, add_bg = TRUE,
diff --git a/man/RunCellQC.Rd b/man/RunCellQC.Rd
index e239d7ed..16b64a88 100644
--- a/man/RunCellQC.Rd
+++ b/man/RunCellQC.Rd
@@ -8,13 +8,13 @@ RunCellQC(
   srt,
   assay = "RNA",
   split.by = NULL,
+  return_filtered = FALSE,
   qc_metrics = c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio",
     "species"),
-  return_filtered = FALSE,
   db_method = "scDblFinder",
   db_rate = NULL,
   db_coefficient = 0.01,
-  outlier_cutoff = c("log10_nCount:lower:2.5", "log10_nCount:higher:5",
+  outlier_threshold = c("log10_nCount:lower:2.5", "log10_nCount:higher:5",
     "log10_nFeature:lower:2.5", "log10_nFeature:higher:5", "featurecount_dist:lower:2.5"),
   outlier_n = 1,
   UMI_threshold = 3000,
@@ -40,18 +40,18 @@ RunCellQC(
 
 \item{split.by}{Name of the sample variable to split the Seurat object. Default is NULL.}
 
+\item{return_filtered}{Logical indicating whether to return a cell-filtered Seurat object. Default is FALSE.}
+
 \item{qc_metrics}{A character vector specifying the quality control metrics to be applied. Default is
 `c("doublets", "outlier", "umi", "gene", "mito", "ribo", "ribo_mito_ratio", "species")`.}
 
-\item{return_filtered}{Logical indicating whether to return a cell-filtered Seurat object. Default is FALSE.}
-
 \item{db_method}{Doublet-calling methods used. Can be one of \code{scDblFinder}, \code{Scrublet}, \code{DoubletDetection}, \code{scds_cxds}, \code{scds_bcds}, \code{scds_hybrid}}
 
 \item{db_rate}{The expected doublet rate. By default this is assumed to be 1\% per thousand cells captured (so 4\% among 4000 thousand cells), which is appropriate for 10x datasets.}
 
 \item{db_coefficient}{The coefficient used to calculate the doublet rate. Default is 0.01. Doublet rate is calculated as`ncol(srt) / 1000 * db_coefficient`}
 
-\item{outlier_cutoff}{A character vector specifying the outlier cutoff values. Default is
+\item{outlier_threshold}{A character vector specifying the outlier threshold. Default is
 `c("log10_nCount:lower:2.5", "log10_nCount:higher:5", "log10_nFeature:lower:2.5", "log10_nFeature:higher:5", "featurecount_dist:lower:2.5")`. See \link[scuttle]{isOutlier}.}
 
 \item{outlier_n}{Minimum number of outlier metrics that meet the conditions for determining outlier cells. Default is 1.}
diff --git a/man/RunUMAP2.Rd b/man/RunUMAP2.Rd
index 3d759b29..fb32bb47 100644
--- a/man/RunUMAP2.Rd
+++ b/man/RunUMAP2.Rd
@@ -19,6 +19,7 @@ RunUMAP2(object, ...)
   slot = "data",
   umap.method = "uwot",
   reduction.model = NULL,
+  n_threads = NULL,
   return.model = FALSE,
   n.neighbors = 30L,
   n.components = 2L,
@@ -45,6 +46,7 @@ RunUMAP2(object, ...)
   assay = NULL,
   umap.method = "uwot",
   reduction.model = NULL,
+  n_threads = NULL,
   return.model = FALSE,
   n.neighbors = 30L,
   n.components = 2L,