remove repetitions, format code, fix bug

R/plot_clustering_QC.R

@@ -1,8 +1,7 @@
-
 # plots heatmap of scores
-plot_cls_score_heatmap <- function(x, type, exposure_thr=0.05) {
+plot_cls_score_heatmap = function(x, type, exposure_thr=0.05) {
 
-  df = get_clusters_score(x, type, exposure_thr) %>% subset(significance == T)
+  scores = get_clusters_score(x, type, exposure_thr) %>% subset(significance==T)
 
   # df2 = significant_signatures(x, types, threshold)
 
@@ -19,84 +18,85 @@ plot_cls_score_heatmap <- function(x, type, exposure_thr=0.05) {
   #     )
   # }
 
-  p = ggplot(data=df, aes(x=cluster, y=signature, fill=round(score, 3), label=round(score, 3))) +
+  p = ggplot(data=scores,
+             aes(x=cluster, y=signature, fill=round(score, 3), label=round(score, 3))) +
     geom_tile(color="white") +
     scale_fill_gradient(low="grey", high="dodgerblue1") +
     geom_text(color="black", size=3) +  # Add text annotations
     # scale_fill_gradient(low="white", high="steelblue") +  # Choose your desired color gradient
     labs(
-      title="Significant signatures in clusters", 
-      subtitle = "(based on clustering scores)", 
+      title="Significant signatures in clusters",
+      subtitle = "(based on clustering scores)",
       x="Clusters",
-      y="Signatures", 
-      fill = "Score") + 
+      y="Signatures",
+      fill = "Score") +
     theme_minimal() +
     theme(
       # remove the vertical grid lines
       panel.grid.major.x=element_blank(),
       # explicitly set the horizontal lines (or they will disappear too)
       panel.grid.major.y=element_line( linewidth=.1, color="black" ),
       #legend.position="none"
-    ) + 
+    ) +
     theme_bw()
 
   return(p)
 }
 
-#===============================================================================
 
-# input : basilica object
-# output: ggplot (samples frequency in clusters)
-plot_cluster_freq = function(x) {
-  df = get_cluster_assignments(x) # dataframe
-  p=ggplot(df, aes(x=clusters)) +
-    geom_bar(stat="count", fill="purple") +
-    labs(title="Distribution of samples in clusters", x="Clusters", y="Number of Samples") +
-    theme_bw()
-  return(p)
-}
+## SAME AS plot_mixture_weights(x, empirical=TRUE)
+# # input : basilica object
+# # output: ggplot (samples frequency in clusters)
+# plot_cluster_freq = function(x) {
+#   df = get_cluster_assignments(x) # dataframe
+#   ggplot(df, aes(x=clusters)) +
+#     geom_bar(stat="count", fill="purple") +
+#     labs(title="Distribution of samples in clusters", x="Clusters", y="Number of Samples") +
+#     theme_bw()
+# }
 
-#===============================================================================
 
+plot_cluster_scores = function(x, type, cluster_label, final_score=TRUE) {
 
-plot_cluster_scores <- function(x, context_type, cluster_label, final_score=TRUE) {
-
-  if ( !(cluster_label %in% get_cluster_labels(x)) ) {
-    warning("invalid cluster label!")
-  }
-
-  scores <- get_clusters_score(x, types = context_type, exposure_thr = 0.05, quantile_thr = 0.9)
-  df = scores %>% subset(type == context_type & cluster == cluster_label)
-
-  if (final_score) {
+  if (!(cluster_label %in% get_cluster_labels(x))) warning("invalid cluster label!")
+
+  scores = get_clusters_score(x, types=type, exposure_thr=0.05, quantile_thr=0.9) %>%
+    subset(type==type & cluster==cluster_label)
+
+  if (final_score==TRUE) {
     # FINAL SCORE
-    p = ggplot(df, aes(x=signature, y=score, color=cluster, group=cluster)) +
+    p = ggplot(scores, aes(x=signature, y=score, color=cluster, group=cluster)) +
       geom_line() +
       geom_point() +
-      geom_hline(yintercept=df$score_quantile, linetype="dashed", color="black") +
-      labs(title=paste0("Signatures Score (Final) in Cluster: ", b), x="Mutational Signature", y="Score") +
+      geom_hline(aes(yintercept=score_quantile), linetype="dashed", color="black") +
+      labs(title=paste0("Signatures scores (final) in cluster ", cluster_label),
+           x="Signature", y="Score") +
       theme(axis.text.x=element_text(angle=90)) +
-      theme_bw() + guides(color = guide_legend(title = "Clustering Scores"))
-  } else if (!final_score) {
+      theme_bw() +
+      guides(color=guide_legend(title="Cluster"))
+
+    return(p)
+
+  } else if (final_score==FALSE) {
     # PARTIAL SCORES
-    df_long = tidyr::pivot_longer(df[c(1,2,3,4,5)],
-                                  cols=c(varRatio, activeRatio, mutRatio),
-                                  names_to="score_title", values_to="value")
-    p <- ggplot(subset(df_long, cluster == cluster_label),
-                aes(x=signature, y=value, color=score_title, group=score_title)) +
+    scores_long = scores %>%
+      dplyr::select(signature, cluster, varRatio, activeRatio, mutRatio) %>%
+      tidyr::pivot_longer(cols=c(varRatio, activeRatio, mutRatio),
+                          names_to="score_title", values_to="value")
+    p = ggplot(subset(scores_long, cluster==cluster_label),
+               aes(x=signature, y=value, color=score_title, group=score_title)) +
       geom_line() +
       geom_point() +
-      labs(
-        title=paste0("Signatures Score (Ingredients) in Cluster: ", cluster_label), 
-        x="Mutational Signature", 
-        y="Value"
-      ) +
-      theme_bw()
-  } else {warning("invalid final_score!")}
-
-  return(p)
-}
+      labs(title=paste0("Signatures scores (partial) in cluster ", cluster_label),
+           x="Signature", y="Score") +
+      theme_bw() +
+      guides(color=guide_legend(title="Score name"))
 
+    return(p)
+
+  } else {cli::cli_abort("Argument `final_score` can be either {TRUE} or {FALSE}")}
+
+}