fix: fix empty groupings for merge_clonal_groupings

Author: pwwang

R/clonalcompositionplot.R

@@ -29,6 +29,7 @@
 #' @importFrom scRepertoire clonalQuant
 #' @export
 #' @examples
+#' \donttest{
 #' set.seed(8525)
 #' data(contig_list, package = "scRepertoire")
 #' data <- scRepertoire::combineTCR(contig_list)
@@ -63,6 +64,7 @@
 #' ClonalVolumePlot(sobj, x = "seurat_clusters")
 #' ClonalVolumePlot(sobj, group_by = "seurat_clusters")
 #' ClonalVolumePlot(sobj, x = "seurat_clusters", plot_type = "box")
+#' }
 ClonalVolumePlot <- function(
     data, clone_call = "aa", chain = "both", scale = FALSE,
     plot_type = c("bar", "box", "violin"), x = "Sample", group_by = NULL,

R/clonalstatplot.R

@@ -39,6 +39,7 @@
 #' If NULL, all the subgroups in `subgroup_by` will be included.
 #' If a vector, the subgroups will be included in the order of the vector for all `groups`.
 #' If a list, the subgroups will be used for each `groups`, with `groups` as the names.
+#' @param within_subgroup Whether to select the clones within each subgroup.
 #' @param subgroups The subgroups to include in the plot. Default is NULL.
 #' @param facet_by The column name in the meta data to facet the plots. Default: NULL.
 #'  This argument is not supported and will raise an error if provided.
@@ -47,6 +48,8 @@
 #' Note that the clones will be ordered by the value of this expression in descending order.
 #' @param y The y-axis variable to use for the plot. Default is NULL.
 #' * For `bar` plot, Either "TotalSize" or "Count" can be used, representing the total size (# cells) of the selected clones or the number of selected clones, respectively.
+#' @param xlab The x-axis label. Default is NULL.
+#' @param ylab The y-axis label. Default is NULL.
 #' @param ... Other arguments passed to the specific plot function.
 #' * For `bar` plot, see [plotthis::BarPlot()].
 #' * For `trend` plot, see [plotthis::TrendPlot()].
@@ -219,7 +222,7 @@ ClonalStatPlot <- function(
         if (length(clones_expr) == 1 && grepl("(", clones_expr, fixed = TRUE) && grepl(")", clones_expr, fixed = TRUE)) {
             selected <- eval(parse(text = clones_expr))
         } else {
-            selected <- filter(data, CloneID %in% clones_expr)
+            selected <- filter(data, !!sym("CloneID") %in% clones_expr)
         }
         if (!is.null(topn)) {
             selected <- slice_head(selected, n = topn)
@@ -278,7 +281,7 @@ ClonalStatPlot <- function(
             pivot_longer(cols = groups, names_to = group_by, values_to = "Size") %>%
             dplyr::filter(!!sym("Size") > 0) %>%
             dplyr::group_by(!!!syms(unique(c("CloneGroups", group_by, subgroup_by, facet_by, split_by)))) %>%
-            summarise(TotalSize = sum(Size), Count = n(), .groups = "drop")
+            summarise(TotalSize = sum(!!sym("Size")), Count = n(), .groups = "drop")
 
         BarPlot(data, x = group_by, y = y %||% "TotalSize", group_by = "CloneGroups", group_name = clone_groups_name,
             facet_by = facet_by, split_by = split_by, xlab = xlab, ylab = ylab, ...)
@@ -322,7 +325,7 @@ ClonalStatPlot <- function(
         data <- data %>% pivot_longer(cols = groups, names_to = group_by, values_to = "Size") %>%
             dplyr::filter(!!sym("Size") > 0) %>%
             dplyr::group_by(!!!syms(unique(c("CloneGroups", group_by, subgroup_by, facet_by, split_by)))) %>%
-            summarise(TotalSize = sum(Size), .groups = "drop")
+            summarise(TotalSize = sum(!!sym("Size")), .groups = "drop")
         TrendPlot(data, x = group_by, y = "TotalSize", group_by = "CloneGroups", group_name = clone_groups_name,
             facet_by = facet_by, split_by = split_by, xlab = xlab, ylab = ylab, ...)
     }

R/clonalutils.R

@@ -81,10 +81,14 @@ merge_clonal_groupings <- function(data, groupings, sep = " // ") {
             warning("The 'Sample' column is not found in the meta data, 'orig.indent' will be used instead.")
             data$Sample <- data$orig.ident
         }
-        samples <- unique(data$Sample)
-        # combine Sample and group_by so that the count/frequency is calculated for each
-        # combined group
-        data@meta.data <- unite(data@meta.data, ".group", !!!syms(groupings), sep = sep, remove = FALSE)
+        # samples <- unique(data$Sample)
+        if (length(groupings) == 0) {
+            data@meta.data$.group <- ""
+        } else {
+            # combine Sample and group_by so that the count/frequency is calculated for each
+            # combined group
+            data@meta.data <- unite(data@meta.data, ".group", !!!syms(groupings), sep = sep, remove = FALSE)
+        }
     } else {
         samples <- names(data)
         data <- lapply(samples, function(s) {
@@ -99,7 +103,12 @@ merge_clonal_groupings <- function(data, groupings, sep = " // ") {
         # combine Sample and group_by so that the count/frequency is calculated for each
         # combined group
         data <- lapply(data, function(d) {
-            unite(d, ".group", !!!syms(groupings), sep = sep, remove = TRUE)
+            if (length(groupings) == 0) {
+                d$.group <- ""
+            } else {
+                d <- unite(d, ".group", !!!syms(groupings), sep = sep, remove = TRUE)
+            }
+            d
         })
     }