Added patch work in suggestion

DESCRIPTION

@@ -17,7 +17,7 @@ Imports:
     assertthat, e1071, dplyr, entropy, ggplot2, igraph, magrittr, maSigPro,
     MASS, MatrixGenerics, methods, parallel, parallelly, plotly, RColorConesa,
     rlang, S4Vectors, scales, shiny, SingleCellExperiment, stats, stringr,
-    utils, ComplexUpset, mclust
+    utils, mclust
 Depends: R (>= 4.0)
 Encoding: UTF-8
 LazyData: true
@@ -27,7 +27,10 @@ Suggests:
     roxygen2,
     knitr,
     rmarkdown,
-    BiocStyle
+    BiocStyle,
+    ComplexUpset,
+    UpSetR,
+    patchwork
 Config/testthat/edition: 3
 URL: https://github.com/BioBam/scMaSigPro/
 biocViews: Clustering, Regression, TimeCourse, DifferentialExpression,

NAMESPACE

@@ -50,10 +50,6 @@ exportMethods(eSparse)
 exportMethods(pathAssign)
 exportMethods(predictors)
 import(ggplot2)
-importFrom(ComplexUpset,intersection_matrix)
-importFrom(ComplexUpset,intersection_size)
-importFrom(ComplexUpset,upset)
-importFrom(ComplexUpset,upset_set_size)
 importFrom(MASS,glm.nb)
 importFrom(MASS,negative.binomial)
 importFrom(MatrixGenerics,rowMeans)
@@ -171,5 +167,6 @@ importFrom(stringr,str_split_i)
 importFrom(utils,View)
 importFrom(utils,combn)
 importFrom(utils,data)
+importFrom(utils,packageVersion)
 importFrom(utils,setTxtProgressBar)
 importFrom(utils,txtProgressBar)

R/plotDiagnostics.R

@@ -53,7 +53,7 @@ plotDiagnostics <- function(scmpObj,
       legend.position = "bottom",
       panel.grid.major = element_line(
         color = "grey90", linewidth = 0.3, linetype = "dashed"
-      ),legend.title = element_text(hjust = 0.5),
+      ),
       panel.grid.minor = element_blank()
     )
 

R/plotIntersect.R

@@ -2,12 +2,12 @@
 #'
 #' @description
 #' Generate UpSet Plot on Intersection of Significant Genes from scMaSigPro
-#' object. It is a wrapper around `ComplexUpset::upset`.
+#' object. It is a wrapper around `ComplexUpset::upset` and `UpSetR::upset`.
 #'
 #' @importFrom S4Vectors isEmpty
-#' @importFrom ComplexUpset upset intersection_matrix intersection_size upset_set_size
 #' @importFrom RColorConesa colorConesa
-#'
+#' @importFrom utils packageVersion
+#' 
 #' @param scmpObj An object of class \code{\link{ScMaSigPro}}.
 #' @param min_intersection_size Minimal number of observations in an intersection
 #' for it to be included.
@@ -16,16 +16,22 @@
 #' @param keep_empty_groups Whether empty sets should be kept (including sets
 #' which are only empty after filtering by size)
 #' @param show_sets_size The overall set sizes plot, e.g. from upset_set_size()
-#' (FALSE to hide)
+#' @param package Which package to use for the UpsetPlot. Options are 'ComplexUpset'
+#' or 'UpSetR' (Default).
+#' @param verbose Print detailed output in the console. (Default is TRUE)
 #'
-#' @return ggplot2 plot object.
+#' @return ggplot2 plot object for 'ComplexUpset' or upset object for 'UpSetR'.
 #'
 #' @author Priyansh Srivastava \email{spriyansh29@@gmail.com}
 #'
 #' @export
-plotIntersect <- function(scmpObj, min_intersection_size = 2,
+plotIntersect <- function(scmpObj,
+                          package = "UpSetR",
+                          min_intersection_size = 2,
                           keep_empty_groups = TRUE,
-                          width_ratio = 0.1, show_sets_size = FALSE) {
+                          width_ratio = 0.1,
+                          show_sets_size = FALSE,
+                          verbose = TRUE) {
   # Check the data
   assert_that(
     is(scmpObj, "ScMaSigPro"),
@@ -37,80 +43,109 @@ plotIntersect <- function(scmpObj, min_intersection_size = 2,
     msg = "'sig.genes@Summary' slot is empty, please run 'sc.get.siggenes'"
   )
 
+  # Check for possible options
+  assert_that(package %in% c("ComplexUpset", "UpSetR"),
+    msg = "Please provide a valid package name for UpSet plot. Options are 'ComplexUpset' or 'UpSetR'"
+  )
+
+  # Check if package is installed
+  if (!requireNamespace(package, quietly = TRUE)) {
+    stop(paste0("Package '", package, "' is not installed. Please install it first."))
+  } else {
+    if (verbose) {
+      message(paste0("Using '", package, "' for UpSet plot."))
+    }
+  }
+
   gene_list <- scmpObj@Significant@genes
-  # Create a unique list of all genes
-  all_genes <- unique(unlist(gene_list))
 
-  # Initialize the data frame
-  gene_df <- data.frame(gene = all_genes)
+  if (package == "UpSetR") {
+    # Create list object
+    upset_r_gene_list <- UpSetR::fromList(gene_list)
 
-  # Add columns for each pathway
-  for (pathway in names(gene_list)) {
-    gene_df[[pathway]] <- gene_df$gene %in% gene_list[[pathway]]
-  }
+    # Create Plot
+    p <- UpSetR::upset(
+      upset_r_gene_list,
+      main.bar.color = "#F58A53",
+      matrix.color = "#15918A",
+      line.size = 1.5,
+      cutoff = min_intersection_size,
+      empty.intersections = keep_empty_groups,
+      point.size = 3,
+      shade.color = "purple",
+      text.scale = 1.5,
+      sets.x.label = "Number of Features",
+      sets.bar.color = "#EE446F"
+    )
+    return(p)
+  } else {
+    # Check version of the ggplot2
+    if (packageVersion("ggplot2") >= "3.5.0") {
+      warning("Please downgrade the ggplot2 to '>= 3.5.0' to use 'ComplesUpset'. We will support the latest version in future.
+          Visit:'https://github.com/krassowski/complex-upset/issues/195' for more details.")
+    } else {
+      # # Create a unique list of all genes
+      all_genes <- unique(unlist(gene_list))
 
-  # Binarize Variables and set factors
-  gene_df[, -1] <- lapply(gene_df[, -1], function(x) as.integer(x))
+      # Initialize the data frame
+      gene_df <- data.frame(gene = all_genes)
 
-  # Get conesa colours
-  col_pal <- colorConesa(3)
+      # Add columns for each pathway
+      for (pathway in names(gene_list)) {
+        gene_df[[pathway]] <- gene_df$gene %in% gene_list[[pathway]]
+      }
 
-  if (show_sets_size) {
-    show_sets_size <- upset_set_size()
-  }
+      # Binarize Variables and set factors
+      gene_df[, -1] <- lapply(gene_df[, -1], function(x) as.integer(x))
+
+      # Get conesa colours
+      col_pal <- colorConesa(3)
 
-  # Create Upset
-  p <- upset(
-    data = gene_df,
-    intersect = colnames(gene_df)[-1],
-    width_ratio = width_ratio,
-    min_size = min_intersection_size,
-    keep_empty_groups = keep_empty_groups,
-    name = "Vars",
-    # wrap=FALSE,
-    set_sizes = show_sets_size,
-    # stripes=c('deepskyblue1'),
-    matrix = (
+      if (show_sets_size) {
+        show_sets_size <- ComplexUpset::upset_set_size()
+      }
 
-      intersection_matrix(
-        geom = geom_point(
-          shape = "square",
-          size = 3.5
+      # Create Upset
+      p <- ComplexUpset::upset(
+        data = gene_df,
+        intersect = colnames(gene_df)[-1],
+        width_ratio = width_ratio,
+        min_size = min_intersection_size,
+        keep_empty_groups = keep_empty_groups,
+        name = "Vars",
+        # wrap=FALSE,
+        set_sizes = show_sets_size,
+        # stripes=c('deepskyblue1'),
+        matrix = (
+
+          ComplexUpset::intersection_matrix(
+            geom = geom_point(
+              shape = "square",
+              size = 3.5
+            ),
+            segment = geom_segment(
+              linetype = "dotted",
+              color = col_pal[1]
+            )
+          )
+          + scale_color_manual(
+              values = c("TRUE" = col_pal[1], "FALSE" = col_pal[3]),
+              # labels=c('TRUE'='yes', 'FALSE'='no'),
+              breaks = c("TRUE", "FALSE")
+            )
         ),
-        segment = geom_segment(
-          linetype = "dotted",
-          color = col_pal[1]
-        )
-      )
-      + scale_color_manual(
-          values = c("TRUE" = col_pal[1], "FALSE" = col_pal[3]),
-          # labels=c('TRUE'='yes', 'FALSE'='no'),
-          breaks = c("TRUE", "FALSE")
+        base_annotations = list(
+          "Intersection size" = ComplexUpset::intersection_size(
+            counts = TRUE,
+            mapping = aes(fill = "bars_color")
+          )
+          + scale_fill_manual(values = c("bars_color" = col_pal[2]), guide = "none")
         )
-    ),
-    base_annotations = list(
-      "Intersection size" = intersection_size(
-        counts = TRUE,
-        mapping = aes(fill = "bars_color")
-      )
-      + scale_fill_manual(values = c("bars_color" = col_pal[2]), guide = "none")
-    )
-  ) + ggtitle("Intersection of features among paths") +
-    theme(legend.position = "none",  legend.title = element_text(hjust = 0.5))
-
-  # return plot
-  return(p)
+      ) + ggtitle("Intersection of features among paths") +
+        theme(legend.position = "none", legend.title = element_text(hjust = 0.5))
 
-  # Perform UpSet plot
-  # upset(
-  #     fromList(gene.list),
-  #     main.bar.color = "#F58A53",
-  #     matrix.color = "#15918A",
-  #     line.size = 1.5,
-  #     point.size = 3,
-  #     shade.color = "purple",
-  #     text.scale = 1.5,
-  #     sets.x.label = "Number of Features",
-  #     sets.bar.color = "#EE446F"
-  # )
+      # return plot
+      return(p)
+    }
+  }
 }

R/plotTrend.R

@@ -201,7 +201,7 @@ plotTrend <- function(scmpObj,
     theme(
       legend.position = "bottom",
       panel.grid.major = element_line(color = "grey90", linewidth = 0.3, linetype = "dashed"),
-      panel.grid.minor = element_blank(), legend.title.align = 0.5 
+      panel.grid.minor = element_blank()
     ) +
     scale_x_continuous(breaks = seq(min(xlim), max(xlim), by = round(log10(length(points.df[[pooled.time]]))))) +
     labs(color = "Paths") +

vignettes/Basic-Workflow.Rmd

@@ -319,7 +319,7 @@ By setting the vars parameter to "groups", the function will add genes with
 $R^2$ >= 0.7 to the object. To explore the number of genes per group, we will 
 make an upset plot:
 ```{r, "uspet",eval=TRUE, echo=TRUE, fig.width=8, fig.height=6}
-plotIntersect(scmp_ob)
+plotIntersect(scmp_ob, package = "ComplexUpset")
 ```
 
 Here, we observe that 23 genes belong to both Path2vsPath1 and Path1, indicating

vignettes/scMaSigPro-Class.Rmd

@@ -20,6 +20,7 @@ vignette: >
 knitr::opts_chunk$set(echo = TRUE)
 knitr::opts_chunk$set(crop = NULL)
 library(scMaSigPro)
+library(patchwork)
 ```
 
 ## Introduction