Added parameter labels to plot_expression_partitions and plot_express…

…ion_frequencies where users can specify labels for each generation

R/utils.R

@@ -181,6 +181,9 @@ get_deg_summary <- function(deg_list) {
 #' @param group_by Character indicating the name of the variable 
 #' in \strong{partition_table} to use to group genes. One of "Category" or
 #' "Class". Default: "Category".
+#' @param labels A character vector of length 3 indicating the labels to be
+#' given for parent 1, offspring, and parent 2. 
+#' Default: \code{c("P1", "F1", "P2")}.
 #'
 #' @return A ggplot object with a scatterplot.
 #' 
@@ -190,7 +193,8 @@ get_deg_summary <- function(deg_list) {
 #' @noRd
 #' 
 partition_scatterplot <- function(
-        partition_table, palette, group_by = "Category"
+        partition_table, palette, group_by = "Category",
+        labels = c("P1", "F1", "P2")
 ) {
 
     p_scatter <- ggplot(
@@ -203,15 +207,15 @@ partition_scatterplot <- function(
         theme_bw() +
         labs(
             subtitle = expression(Log[2] ~ "fold change between generations"),
-            x = "F1 vs P1",
-            y = "F1 vs P2"
+            x = paste0(labels[2], " vs ", labels[1]), # F1 vs P1
+            y = paste0(labels[2], " vs ", labels[3]) # F1 vs P2
         ) +
         ggplot2::theme(
             panel.grid = ggplot2::element_blank(),
             axis.text = element_text(size = 11)
         ) +
         geom_vline(xintercept = 0, linetype = "dashed") +
-        geom_hline(yintercept = 0, linetype = "dashed")
+        geom_hline(yintercept = 0, linetype = "dashed") 
 
     return(p_scatter)
 }
@@ -227,6 +231,9 @@ partition_scatterplot <- function(
 #' @param group_by Character indicating the name of the variable 
 #' in \strong{partition_table} to use to group genes. One of "Category" or
 #' "Class". Default: "Category".
+#' @param labels A character vector of length 3 indicating the labels to be
+#' given for parent 1, offspring, and parent 2. 
+#' Default: \code{c("P1", "F1", "P2")}.
 #'
 #' @return A list of ggplot objects with line plots.
 #' 
@@ -236,7 +243,8 @@ partition_scatterplot <- function(
 #' @noRd
 #' 
 partition_lineplots <- function(
-        partition_table, palette, add_n = TRUE, group_by = "Category"
+        partition_table, palette, add_n = TRUE, group_by = "Category",
+        labels = c("P1", "F1", "P2")
 ) {
 
     # Data frame of point coordinates for each group
@@ -286,7 +294,11 @@ partition_lineplots <- function(
                 axis.text.x = element_text(size = 11, face = "bold"),
                 axis.text.y = element_blank()
             ) +
-            ylim(c(0, 4))
+            ylim(c(0, 4)) +
+            scale_x_discrete(
+                breaks = c("P1", "F1", "P2"),
+                labels = labels
+            )
 
         if(group_by == "Class") { p <- p + facet_wrap("Category") }
 

R/visualization.R

@@ -95,6 +95,9 @@ plot_expression_triangle <- function(
 #' If \strong{group_by = "Category"}, this must be a vector of length 12.
 #' If \strong{group_by = "Class"}, this must be a vector of length 5.
 #' If NULL, a default color palette will be used.
+#' @param labels A character vector of length 3 indicating the labels to be
+#' given for parent 1, offspring, and parent 2. 
+#' Default: \code{c("P1", "F1", "P2")}.
 #'
 #' @return A ggplot object with a plot showing genes in each expression
 #' partition.
@@ -108,7 +111,8 @@ plot_expression_triangle <- function(
 #' partition_table <- expression_partitioning(deg_list)
 #' plot_expression_partitions(partition_table)
 plot_expression_partitions <- function(
-        partition_table, group_by = "Category", palette = NULL
+        partition_table, group_by = "Category", palette = NULL,
+        labels = c("P1", "F1", "P2")
 ) {
 
     pdata <- partition_table
@@ -118,10 +122,14 @@ plot_expression_partitions <- function(
     names(pal) <- levels(pdata[[group_by]])
 
     # 1) Create scatterplot
-    p_scatter <- partition_scatterplot(pdata, pal, group_by = group_by)
+    p_scatter <- partition_scatterplot(
+        pdata, pal, group_by = group_by, labels = labels
+    )
 
     # 2) Create line plots to represent partitions
-    p_line <- partition_lineplots(pdata, pal, group_by = group_by)
+    p_line <- partition_lineplots(
+        pdata, pal, group_by = group_by, labels = labels
+    )
 
     # Combine figures
     if(group_by == "Class") {
@@ -164,6 +172,9 @@ plot_expression_partitions <- function(
 #' If \strong{group_by = "Category"}, this must be a vector of length 12.
 #' If \strong{group_by = "Class"}, this must be a vector of length 5.
 #' If NULL, a default color palette will be used.
+#' @param labels A character vector of length 3 indicating the labels to be
+#' given for parent 1, offspring, and parent 2. 
+#' Default: \code{c("P1", "F1", "P2")}.
 #' 
 #' @return A ggplot object with a barplot showing gene frequencies per
 #' partition next to explanatory line plots depicting each partition.
@@ -177,7 +188,8 @@ plot_expression_partitions <- function(
 #' partition_table <- expression_partitioning(deg_list)
 #' plot_partition_frequencies(partition_table)
 plot_partition_frequencies <- function(
-        partition_table, group_by = "Category", palette = NULL
+        partition_table, group_by = "Category", palette = NULL,
+        labels = c("P1", "F1", "P2")
 ) {
 
     # Define color palette
@@ -209,7 +221,8 @@ plot_partition_frequencies <- function(
 
     # Get line plots
     p_line <- partition_lineplots(
-        partition_table, pal, add_n = FALSE, group_by = group_by
+        partition_table, pal, add_n = FALSE, group_by = group_by,
+        labels = labels
     )
 
     # Combine plots