Merge pull request #346 from atrigila/add_plots

Add plots by biotype

CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- [[#345](https://github.com/nf-core/differentialabundance/pull/345)] - Plot differentially expressed genes by gene biotype ([@atrigila](https://github.com/atrigila), review by [@grst](https://github.com/grst))
 - [[#343](https://github.com/nf-core/differentialabundance/pull/343)] - Add pipeline-level nf-tests ([@atrigila](https://github.com/atrigila), review by [@pinin4fjords](https://github.com/pinin4fjords) and [@nschcolnicov](https://github.com/nschcolnicov))
 - [[#286](https://github.com/nf-core/differentialabundance/pull/286)] - Integration of limma voom for rnaseq data ([@KamilMaliszArdigen](https://github.com/KamilMaliszArdigen), review by [@pinin4fjords](https://github.com/pinin4fjords))
 

assets/differentialabundance_report.Rmd

@@ -895,6 +895,25 @@ for (i in 1:nrow(contrasts)){
         if (nrow(contrast_de) > 0){
             contrast_de <- round_dataframe_columns(contrast_de, digits=params$report_round_digits)
             print( htmltools::tagList(datatable(contrast_de, caption = paste('Differential genes', dir, 'in', contrast_descriptions[i], " (check", differential_files[[i]], "for more detail)"), rownames = FALSE) ))
+
+        # Plot Differentially Expressed Genes by Gene Biotype
+        gene_biotype_table <- contrast_de %>%
+            group_by(`Gene biotype`) %>%
+            summarise(count = dplyr::n(), .groups = 'drop') %>%
+            filter(count > 0) %>%
+            arrange(desc(count))
+
+        gene_biotype_plot <- ggplot(gene_biotype_table, aes(x = reorder(`Gene biotype`, -count), y = count)) +
+            geom_bar(stat = "identity", position = position_dodge()) +
+            labs(
+                title = paste0("Differentially Expressed Genes by Gene Biotype (", dir, ")"),
+                x = "Gene Biotype",
+                y = "Number of Differentially Expressed Genes"  ) +
+            theme_minimal() +
+            theme(axis.text.x = element_text(angle = 45, hjust = 1))
+
+        print(gene_biotype_plot)
+
         }else{
             cat(paste0("No significantly differential '", dir, "' genes.\n\n"))
         }