removed entrypoint

Author: rela-v

Dockerfile

@@ -34,4 +34,4 @@ RUN R -e "renv::restore(library='/opt/renv/library')"
 COPY . .
 
 # 6. Execution Logic
-ENTRYPOINT ["R", "--vanilla", "-e", "bookdown::render_book(\"index.Rmd\")"]
+# ENTRYPOINT ["R", "--vanilla", "-e", "bookdown::render_book(\"index.Rmd\")"]

Rmd/paver_report.Rmd

@@ -24,5 +24,133 @@ x + ggprism::theme_prism(base_size = 9)
 ### Heatmap Plot
 
 ```{r}
-x <- quiet(PAVER::PAVER_hunter_plot(.[[1]], unit = .[[2]]))
-```
+#' PAVER_hunter_plot
+#'
+#' This function takes a PAVER result object and generates a heatmap of the enrichment analysis
+#' with clustering and color-coded values based on the direction of regulation.
+#'
+#' @param PAVER_result a list containing the output of PAVER analysis
+#' @param unit optionally, the unit of enrichment analysis for the figure legend title.
+#' @param show_row_titles a logical indicating whether to show row titles in the heatmap.
+#'
+#' @return A heatmap of the expression data with clustering and color-coded values based on the direction of regulation.
+#'
+#' @export
+PAVER_hunter_plot <- function(PAVER_result, unit = NULL, show_row_titles = TRUE) {
+  data <- PAVER_result$prepared_data %>%
+    tidyr::pivot_wider(
+      names_from = "Group",
+      values_from = c("value"),
+      id_cols = "GOID"
+    ) %>%
+    dplyr::inner_join(
+      PAVER_result$clustering %>%
+        dplyr::select(.data$GOID, .data$Cluster),
+      by = "GOID"
+    ) %>%
+    dplyr::mutate(Cluster = forcats::fct_drop(.data$Cluster)) %>%
+    dplyr::mutate(dplyr::across(
+      .cols = dplyr::where(is.numeric),
+      .fns = ~ tidyr::replace_na(.x, 0)
+    )) %>%
+    dplyr::distinct(.data$GOID, .keep_all = TRUE)
+
+  mat <- data %>%
+    dplyr::select(dplyr::where(is.numeric)) %>%
+    as.matrix()
+
+  min <- min(mat, na.rm = T)
+  max <- max(mat, na.rm = T)
+
+  if (nlevels(PAVER_result$prepared_data$Direction) != 1) {
+    col_fun <- circlize::colorRamp2(c(min, 0, max), c("blue", "white", "red"))
+    at <- c(min, 0, max)
+    labels <- c(round(min, 2), 0, round(max, 2))
+  } else {
+    at <- c(min, max)
+    labels <- c(round(min, 2), round(max, 2))
+    if (levels(PAVER_result$prepared_data$Direction) == "+") {
+      col_fun <- circlize::colorRamp2(c(min, max), c("white", "red"))
+    } else {
+      col_fun <- circlize::colorRamp2(c(min, max), c("white", "blue"))
+    }
+  }
+
+  lgd <- ComplexHeatmap::Legend(
+    col_fun = col_fun,
+    title = unit,
+    at = at,
+    labels = labels,
+    direction = "horizontal",
+    title_position = "lefttop",
+    title_gp = grid::gpar(fontsize = 8, fontface = "bold"),
+    labels_gp = grid::gpar(fontsize = 8, fontface = "bold"),
+    legend_width = grid::unit(1, "cm"),
+  )
+
+  c_data <- mat %>% t()
+
+  if (ncol(mat) >= 1) {
+    c_data <- rbind(c_data, c_data)
+  }
+
+  dend <- ComplexHeatmap::cluster_within_group(c_data, data$Cluster)
+
+  color_order <- data[stats::order.dendrogram(dend), ]$Cluster %>%
+    forcats::fct_inorder() %>%
+    levels()
+
+  plot_colors <- PAVER_result$colors %>%
+    magrittr::set_names(levels(data$Cluster))
+
+  plot_colors <- plot_colors[color_order]
+
+  cluster_annotation <- ComplexHeatmap::rowAnnotation(
+    Cluster = ComplexHeatmap::anno_block(gp = grid::gpar(fill = plot_colors)),
+    width = grid::unit(.25, "cm")
+  )
+
+  args <- list(
+    matrix = mat,
+    col = col_fun,
+    left_annotation = cluster_annotation,
+    row_title_gp = grid::gpar(fontsize = 8, fontface = "bold"),
+    column_names_gp = grid::gpar(fontsize = 8, fontface = "bold"),
+    # --- EDITED SECTION START ---
+    column_names_rot = 90,           # Changed from 0 to 90 for vertical labels
+    column_names_centered = FALSE,    # Setting to FALSE often looks better with rotation
+    column_names_side = "bottom",    # Ensures labels are at the bottom of the columns
+    # --- EDITED SECTION END ---
+    row_title_rot = 0,
+    row_title_side = "right",
+    row_gap = grid::unit(1, "mm"),
+    show_row_dend = FALSE,
+    show_column_dend = FALSE,
+    cluster_rows = dend,
+    cluster_columns = ncol(mat) >= 3,
+    split = nlevels(data$Cluster),
+    show_heatmap_legend = FALSE,
+    border = TRUE,
+    row_title = NULL
+  )
+
+  if (show_row_titles) {
+    args$row_title <- character()
+  }
+
+  ht <- do.call(ComplexHeatmap::Heatmap, args)
+
+  ht_draw <- ComplexHeatmap::draw(
+    ht,
+    heatmap_legend_list = lgd,
+    heatmap_legend_side = "bottom",
+    padding = grid::unit(c(1, 1, 5, 1), "mm") # Increased bottom padding for vertical labels
+  )
+
+  plot <- grid::grid.grabExpr(ComplexHeatmap::draw(ht_draw)) %>%
+    ggplotify::as.ggplot()
+
+  plot
+}
+x <- quiet(PAVER_hunter_plot(.[[1]], unit = .[[2]]))
+```

configuration.yml

@@ -6,12 +6,15 @@ gmt: Human_GOALL_with_GO_iea_March_01_2025_symbol.gmt # [Human, Rat, Mouse]
 use_fdr: true # [true, false] Set to true to show FDR line, false for raw p-value
 
 data:
-  - group1: DA
-    group2: CA
-    file: DAvsCA.csv
-  - group1: DB
-    group2: CB
-    file: DBvsCB.csv
+  - group1: F_PL
+    group2: F_CTL
+    file: 3Pod_extdata/lorena_stress/Female_PL_control_vs_SPS_DESeq2.csv
+
+  - group1: M_PL
+    group2: M_CTL
+    file: 3Pod_extdata/lorena_stress/Male_PL_control_vs_SPS_DESeq2.csv
+
+
 # design: design.csv
 # counts: counts.csv