@@ -13,7 +13,7 @@ Authors@R:

         ),

         person(

             given = "Lucas",

-            family = "Prost",

+            family = "Prost-Boxoen",

             role = "aut",

             comment = c(ORCID = "0000-0003-2779-9097")

         ),

@@ -7,7 +7,7 @@

 #' @return A data with the following variables:

 #' \describe{

 #'   \item{Gene}{Character, gene ID.}

-#'   \item{Group}{Factor, expression group. Group names are numbers from

+#'   \item{Category}{Factor, expression group. Category names are numbers from

 #'   1 to 12.}

 #'   \item{Class}{Factor, expression group class. One of "UP" (transgressive

 #'   up-regulation), "DOWN" (transgressive down-regulation), 

@@ -52,7 +52,7 @@ expression_partitioning <- function(deg_list) {

             "unchanged-down-down",

             "up-down-down"

         ),

-        Group = factor(c(1:12), levels = 1:12),

+        Category = factor(c(1:12), levels = 1:12),

         Class = factor(cl, levels = c("UP", "DOWN", "ADD", "ELD_P1", "ELD_P2"))

     )

@@ -74,9 +74,9 @@ expression_partitioning <- function(deg_list) {

     )

     # Combine classification data frame with log2foldchange

-    class_df <- merge(classified_genes[, c("Gene", "Group", "Class")], log2fc_df)

-    class_df <- class_df[!is.na(class_df$Group), ]

-    class_df <- class_df[order(class_df$Group), ]

+    class_df <- merge(classified_genes[, c("Gene", "Category", "Class")], log2fc_df)

+    class_df <- class_df[!is.na(class_df$Category), ]

+    class_df <- class_df[order(class_df$Category), ]

     rownames(class_df) <- NULL

@@ -179,8 +179,8 @@ get_deg_summary <- function(deg_list) {

 #' as returned by \code{expression_partitioning()}.

 #' @param palette A character vector with the color palette to use.

 #' @param group_by Character indicating the name of the variable 

-#' in \strong{partition_table} to use to group genes. One of "Group" or

-#' "Class". Default: "Group".

+#' in \strong{partition_table} to use to group genes. One of "Category" or

+#' "Class". Default: "Category".

 #'

 #' @return A ggplot object with a scatterplot.

 #' 

@@ -189,7 +189,9 @@ get_deg_summary <- function(deg_list) {

 #' @importFrom rlang .data

 #' @noRd

 #' 

-partition_scatterplot <- function(partition_table, palette, group_by = "Group") {

+partition_scatterplot <- function(

+        partition_table, palette, group_by = "Category"

+) {

     p_scatter <- ggplot(

         partition_table, aes(x = .data$lFC_F1_vs_P1, y = .data$lFC_F1_vs_P2)

@@ -223,8 +225,8 @@ partition_scatterplot <- function(partition_table, palette, group_by = "Group")

 #' @param add_n Logical indicating whether to include number of genes in each

 #' group or not. Default: TRUE.

 #' @param group_by Character indicating the name of the variable 

-#' in \strong{partition_table} to use to group genes. One of "Group" or

-#' "Class". Default: "Group".

+#' in \strong{partition_table} to use to group genes. One of "Category" or

+#' "Class". Default: "Category".

 #'

 #' @return A list of ggplot objects with line plots.

 #' 

@@ -234,12 +236,12 @@ partition_scatterplot <- function(partition_table, palette, group_by = "Group")

 #' @noRd

 #' 

 partition_lineplots <- function(

-        partition_table, palette, add_n = TRUE, group_by = "Group"

+        partition_table, palette, add_n = TRUE, group_by = "Category"

 ) {

     # Data frame of point coordinates for each group

     pline_data <- data.frame(

-        Group = factor(rep(1:12, each = 3)),

+        Category = factor(rep(1:12, each = 3)),

         Class = factor(

             rep(c(

                 "ADD", "ELD_P1", "DOWN", "ELD_P2", "UP", "UP", 

@@ -267,7 +269,7 @@ partition_lineplots <- function(

     pline_data <- split(pline_data, pline_data[[group_by]])

     ## Number of genes per level of `group_by`

-    n <- as.numeric(table(partition_table$Group))

+    n <- as.numeric(table(partition_table$Category))

     p_line <- lapply(seq_along(pline_data), function(x) {

@@ -286,7 +288,7 @@ partition_lineplots <- function(

             ) +

             ylim(c(0, 4))

-        if(group_by == "Class") { p <- p + facet_wrap("Group") }

+        if(group_by == "Class") { p <- p + facet_wrap("Category") }

         return(p)

     })

@@ -88,11 +88,11 @@ plot_expression_triangle <- function(

 #' @param partition_table A data frame with genes per expression partition

 #' as returned by \code{expression_partitioning()}.

 #' @param group_by Character indicating the name of the variable 

-#' in \strong{partition_table} to use to group genes. One of "Group" or

-#' "Class". Default: "Group".

+#' in \strong{partition_table} to use to group genes. One of "Category" or

+#' "Class". Default: "Category".

 #' @param palette Character vector with color names to be used for each level

 #' of the variable specified in \strong{group_by}. 

-#' If \strong{group_by = "Group"}, this must be a vector of length 12.

+#' 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.

 #'

@@ -108,7 +108,7 @@ plot_expression_triangle <- function(

 #' partition_table <- expression_partitioning(deg_list)

 #' plot_expression_partitions(partition_table)

 plot_expression_partitions <- function(

-        partition_table, group_by = "Group", palette = NULL

+        partition_table, group_by = "Category", palette = NULL

 ) {

     pdata <- partition_table

@@ -158,11 +158,11 @@ plot_expression_partitions <- function(

 #' @param partition_table A data frame with genes per expression partition

 #' as returned by \code{expression_partitioning()}.

 #' @param group_by Character indicating the name of the variable 

-#' in \strong{partition_table} to use to group genes. One of "Group" or

-#' "Class". Default: "Group".

+#' in \strong{partition_table} to use to group genes. One of "Category" or

+#' "Class". Default: "Category".

 #' @param palette Character vector with color names to be used for each level

 #' of the variable specified in \strong{group_by}. 

-#' If \strong{group_by = "Group"}, this must be a vector of length 12.

+#' 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.

 #' 

@@ -178,7 +178,7 @@ plot_expression_partitions <- function(

 #' partition_table <- expression_partitioning(deg_list)

 #' plot_partition_frequencies(partition_table)

 plot_partition_frequencies <- function(

-        partition_table, group_by = "Group", palette = NULL

+        partition_table, group_by = "Category", palette = NULL

 ) {

     # Define color palette

@@ -189,21 +189,21 @@ plot_partition_frequencies <- function(

     # Get barplot data

     freqs <- table(partition_table[[group_by]])

     freq_df <- data.frame(

-        Group = factor(names(freqs), levels = names(freqs)), 

+        Category = factor(names(freqs), levels = names(freqs)), 

         N = as.numeric(freqs)

     )

     freq_df$Perc <- paste0(round((freq_df$N / sum(freq_df$N)) * 100, 2), "%")

     ymax <- round(max(freq_df$N) + mean(freq_df$N), -2)

     # Create barplot

-    p_bar <- ggplot(freq_df, aes(x = .data$Group, y = .data$N)) +

+    p_bar <- ggplot(freq_df, aes(x = .data$Category, y = .data$N)) +

         geom_bar(fill = pal, color = "gray20", stat = "identity") +

         geom_text(aes(label = .data$Perc), hjust = -0.2) +

         theme_bw() +

         scale_y_continuous(limits = c(0, ymax), expand = c(0, 0)) +

         theme(plot.subtitle = element_text(size = 13)) +

         labs(y = "Count", subtitle = "Frequency of genes per partition") +

-        scale_x_discrete(limits = rev(levels(freq_df$Group))) +

+        scale_x_discrete(limits = rev(levels(freq_df$Category))) +

         coord_flip() 

@@ -213,7 +213,7 @@ plot_partition_frequencies <- function(

     )

     # Combine plots

-    ncols <- ifelse(group_by == "Group", 2, 1)

+    ncols <- ifelse(group_by == "Category", 2, 1)

     p_final <- wrap_plots(

         wrap_plots(p_line, ncol = ncols) & 

             theme(plot.margin = unit(rep(1, 4), "pt")),

@@ -14,7 +14,7 @@ differentially expressed genes as returned by \code{get_deg_list()}.}

 A data with the following variables:

 \describe{

 \item{Gene}{Character, gene ID.}

-\item{Group}{Factor, expression group. Group names are numbers from

+\item{Category}{Factor, expression group. Category names are numbers from

 1 to 12.}

 \item{Class}{Factor, expression group class. One of "UP" (transgressive

 up-regulation), "DOWN" (transgressive down-regulation),

@@ -4,19 +4,23 @@

 \alias{plot_expression_partitions}

 \title{Plot expression partitions}

 \usage{

-plot_expression_partitions(partition_table, group_by = "Group", palette = NULL)

+plot_expression_partitions(

+  partition_table,

+  group_by = "Category",

+  palette = NULL

+)

 }

 \arguments{

 \item{partition_table}{A data frame with genes per expression partition

 as returned by \code{expression_partitioning()}.}

 \item{group_by}{Character indicating the name of the variable

-in \strong{partition_table} to use to group genes. One of "Group" or

-"Class". Default: "Group".}

+in \strong{partition_table} to use to group genes. One of "Category" or

+"Class". Default: "Category".}

 \item{palette}{Character vector with color names to be used for each level

 of the variable specified in \strong{group_by}.

-If \strong{group_by = "Group"}, this must be a vector of length 12.

+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.}

 }

@@ -4,19 +4,23 @@

 \alias{plot_partition_frequencies}

 \title{Plot a barplot of gene frequencies per expression partition}

 \usage{

-plot_partition_frequencies(partition_table, group_by = "Group", palette = NULL)

+plot_partition_frequencies(

+  partition_table,

+  group_by = "Category",

+  palette = NULL

+)

 }

 \arguments{

 \item{partition_table}{A data frame with genes per expression partition

 as returned by \code{expression_partitioning()}.}

 \item{group_by}{Character indicating the name of the variable

-in \strong{partition_table} to use to group genes. One of "Group" or

-"Class". Default: "Group".}

+in \strong{partition_table} to use to group genes. One of "Category" or

+"Class". Default: "Category".}

 \item{palette}{Character vector with color names to be used for each level

 of the variable specified in \strong{group_by}.

-If \strong{group_by = "Group"}, this must be a vector of length 12.

+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.}

 }

@@ -68,7 +68,7 @@ test_that("get_deg_summary() returns a data frame with DE summary", {

 test_that("partition_scatterplot() creates a scatterplot", {

     p1 <- partition_scatterplot(partition_table, palette_class, "Class")

-    p2 <- partition_scatterplot(partition_table, palette_group, "Group")

+    p2 <- partition_scatterplot(partition_table, palette_group, "Category")

     expect_true(is(p1, "ggplot"))

 })

@@ -24,7 +24,7 @@ test_that("plot_expression_triangle() returns a ggplot object", {

 test_that("plot_expression_partitions() returns a multi-panel ggplot", {

-    p1 <- plot_expression_partitions(ptable, group_by = "Group")

+    p1 <- plot_expression_partitions(ptable, group_by = "Category")

     p2 <- plot_expression_partitions(ptable, group_by = "Class")

     expect_true(is(p1, "ggplot"))

@@ -33,7 +33,7 @@ test_that("plot_expression_partitions() returns a multi-panel ggplot", {

 test_that("plot_partition_frequencies() returns a multi-panel ggplot", {

-    p1 <- plot_partition_frequencies(ptable, group_by = "Group")

+    p1 <- plot_partition_frequencies(ptable, group_by = "Category")

     p2 <- plot_partition_frequencies(ptable, group_by = "Class")

     expect_true(is(p1, "ggplot"))