Bug fixes and addition of do_RankedExpressionPlot().

NAMESPACE

@@ -10,7 +10,6 @@ export(do_ChordDiagramPlot)
 export(do_ColorPalette)
 export(do_CopyNumberVariantPlot)
 export(do_CorrelationPlot)
-export(do_DiffusionMapPlot)
 export(do_DimPlot)
 export(do_DotPlot)
 export(do_EnrichmentHeatmap)
@@ -23,6 +22,8 @@ export(do_LoadingsPlot)
 export(do_MetadataPlot)
 export(do_NebulosaPlot)
 export(do_PathwayActivityPlot)
+export(do_RankedEnrichmentPlot)
+export(do_RankedExpressionPlot)
 export(do_RidgePlot)
 export(do_SCEnrichmentHeatmap)
 export(do_SCExpressionHeatmap)

NEWS.md

@@ -1,32 +1,39 @@
 # SCpbur v2.0.3 (In Development)
 
 ## Added functions
--   `do_WafflePlot()`: This function displays proportions as a pictogram grid of 10x10 tiles. It helps to visually see at a glance the proportions of your data. This fails to correctly convey decimal proportions and completely ignores heavily under-represented classes in your dataset.
+-   `do_WafflePlot()`: This function displays proportions as a pictogram grid of 10x10 tiles. It helps to visually see at a glance the proportions of your data. This fails to correctly convey decimal proportions and completely ignores heavily under-represented classes in your dataset. 
+-   `do_RankedExpressionPlot()` to plot expression values as a heatmap along a diffusion component.
 
 ## Removed functions
 -   `do_FunctionalAnnotationPlot()`.
 -   `do_GroupedGOTermPlot()`.
 
 The reason behind it is that they, together with do_TermEnrichmentPlot() targetted the same analysis and, therefore, were redundant.
 
+## Renamed functions
+-   `do_DiffusionMapPlot()` is now called `do_RankedEnrichmentPlot()`. As it now accepts any dimensional reduction and not only diffusion maps.
+
 ## Heavily modified functions.
 -   `do_TermEnrichmentPlot()`: Recoded the whole function. Now accepts the result of using `clusterProfiler::enrichGO()`, `clusterProfiler::enrichKEGG()`, etc. The output is a dot plot with the terms on the Y axis, the Gene Ratio in the X, colored by the adjusted p-value and size mapped to the Gene Count.
 -   `do_DotPlot()`: Removed dependencies with `Seurat::DotPlot()`.
--   `do_DiffusionMapPlot()`, `do_EnrichmentHeatmap()` and `do_SCEnrichmentHeatmap()` do not longer accept `flavor = "AUCell"` due to dependency issues and lack of development support.
+-   `do_RankedEnrichmentPlot()`, `do_EnrichmentHeatmap()` and `do_SCEnrichmentHeatmap()` do not longer accept `flavor = "AUCell"` due to dependency issues and lack of development support.
 
 The reason of these modification is to allow for a much clearer and concise output than before.
 
 ## do_AlluvialPlot()
 -   Enforced a minimum version of `ggalluvial` to deal with deprecation of functions from `dplyr` and `tidyr` that were still used in `ggalluvial` functions.
 
 ## do_BoxPlot()
--   Added `legend.ncol`, `legend.nrow` and `legend.byrow` parameters to control legend behaviour.
+-   Added `legend.ncol`, `legend.nrow` and `legend.byrow` parameters to control legend behavior.
+-   Fixed a bug in which `map_signif_levels` would only accept a logical and not custom mappings.
+-   When `map_signif_levels` is used, the mapping now appears as a plot legend for clarity.
 
 ## do_CopyNumberVariantPlot()
 -   Added `include_chr_arms` parameter to decide whether the heatmap should include a breakdown of the arms or just keep it by chromosomes.
 
 ## do_DimPlot()
 -   Fixed a bug caused by using `cells.highlight` with only one cell.
+-   Fixed a bug causing the "Combined" plot resulting of the use of `split.by` and `group.by` to have a different size than the rest of panels when `ncol` parameter was also used.
 -   Fixed a bug causing a "selected_cells" plot title to show up when using `cells.highlight` and `idents.highlight`. 
 -   Changed the plot title of the "Combined" plot to either `group.by` or `split.by` depending of the usage context.
 -   Added `split.by.combined` parameter and set its default value to `TRUE`. This allows to toggle on or off whether to display the combined view when `split.by` is used.
@@ -56,6 +63,11 @@ The reason of these modification is to allow for a much clearer and concise outp
 
 ## do_ViolinPlot()
 -   Added `order` parameter to reorder the groups based on the median. Only works when `split.by` is set to `NULL`.
+-   Fixed typos in error logging.
+-   Fixed a bug in which color palettes would not display by default when using `split.by`.
+
+## do_VolcanoPlot()
+-   Fixed an issue in which tags would be duplicated when using `use_labels = TRUE` in combination with `order_tabs_by = "both"`.
 
 # SCpbur v2.0.2
 

R/do_BoxPlot.R

@@ -53,7 +53,7 @@ do_BoxPlot <- function(sample,
                        use_test = FALSE,
                        comparisons = NULL,
                        test = "wilcox.test",
-                       map_signif_level = TRUE,
+                       map_signif_level = c("***" = 0.001, "**" = 0.01, "*" = 0.05),
                        plot.title.face = "bold",
                        plot.subtitle.face = "plain",
                        plot.caption.face = "italic",
@@ -79,7 +79,6 @@ do_BoxPlot <- function(sample,
                        "plot.grid" = plot.grid,
                        "order" = order,
                        "use_silhouette" = use_silhouette,
-                       "map_signif_level" = map_signif_level,
                        "legend.byrow" = legend.byrow)
   check_type(parameters = logical_list, required_type = "logical", test_function = is.logical)
   # Check numeric parameters.
@@ -213,7 +212,21 @@ do_BoxPlot <- function(sample,
                                          crayon_key("order"),
                                          crayon_body(".")))
   }
-
+
+
+  if (!is.null(map_signif_level)){
+    assertthat::assert_that(base::isTRUE(is.logical(map_signif_level) | is.numeric(map_signif_level)),
+                            msg = paste0(add_cross(), crayon_body("Parameter "),
+                                         crayon_key("map_signif_level"),
+                                         crayon_body(" needs to be a "),
+                                         crayon_key("logical"),
+                                         crayon_body(" or a "),
+                                         crayon_key("custom mapping"),
+                                         crayon_body(" such as "),
+                                         crayon_key('c("***" = 0.001, "**" = 0.01, "*" = 0.05)'),
+                                         crayon_body(".")))
+  }
+
   if (isTRUE(use_silhouette) & is.null(split.by)){
     p <- data %>%
          ggplot2::ggplot(mapping = ggplot2::aes(x = .data[["group.by"]],
@@ -317,6 +330,14 @@ do_BoxPlot <- function(sample,
                                  textsize = font.size - 8,
                                  family = font.type,
                                  fontface = "bold")
+
+      if (!is.logical(map_signif_level)){
+        caption <- c()
+        for (i in seq_len(length(map_signif_level))){caption <- append(caption, paste0(names(map_signif_level)[i], " = ", format(map_signif_level[i], scientific = FALSE)))}
+        caption <- paste(caption, collapse = ", ")
+
+        p <- p + ggplot2::labs(caption = caption)
+      }
     } else {
       stop(paste0(add_cross(), crayon_body("Please provide the pair of groups to test.")), call. = FALSE)
     }

R/do_DotPlot.R

@@ -275,7 +275,7 @@ do_DotPlot <- function(sample,
       if (isTRUE(cluster)){
         row_order <- rownames(data.cluster)[stats::hclust(stats::dist(data.cluster, method = "euclidean"), method = "ward.D")$order]
       } else {
-        row_order <- rownames(data.cluster)
+        row_order <- features
       }
     }
 
@@ -286,7 +286,11 @@ do_DotPlot <- function(sample,
       if (isTRUE(cluster)){
         col_order <- colnames(data.cluster)[stats::hclust(stats::dist(t(data.cluster), method = "euclidean"), method = "ward.D")$order]
       } else {
-        col_order <- colnames(data.cluster)
+        if (is.factor(sample@meta.data[, group.by])){
+          col_order <- levels(sample@meta.data[, group.by])
+        } else {
+          col_order <- sort(unique(sample@meta.data[, group.by])) 
+        }
       }
     }
 

R/do_FeaturePlot.R

@@ -989,7 +989,7 @@ do_FeaturePlot <- function(sample,
     }
 
     # Generate the final plot with patchwork and use the "ncol" parameter value for the number of columns.
-    p <- patchwork::wrap_plots(list.plots, nrow = 1)
+    p <- patchwork::wrap_plots(list.plots, nrow = ncol)
 
   }