fixes #39

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: pathfindR
 Type: Package
 Title: Enrichment Analysis Utilizing Active Subnetworks
-Version: 1.5.0.9005
+Version: 1.5.0.9006
 Authors@R: c(person("Ege", "Ulgen",
                     role = "cre", 
                     email = "[email protected]",

NEWS.md

@@ -1,4 +1,4 @@
-# pathfindR 1.5.0.9005
+# pathfindR 1.5.0.9006
 ## to be released as 1.5.0
 
 ## Major Changes

R/visualization_functions.R

@@ -1050,10 +1050,19 @@ term_gene_heatmap <- function(result_df, genes_df, num_terms = 10,
                     which(colnames(result_df) == "Up_regulated"))
   down_genes <- apply(result_df, 1, parse_genes,
                       which(colnames(result_df) == "Down_regulated"))
+
+  if (length(down_genes) == 0) {
+    down_genes <- rep(NA, nrow(result_df))
+  }
+  if (length(up_genes) == 0) {
+    up_genes <- rep(NA, nrow(result_df))
+  }
+
   names(up_genes) <- names(down_genes) <- result_df[, ID_column]
 
   ############ Create terms-by-genes matrix and order
   all_genes <- unique(c(unlist(up_genes), unlist(down_genes)))
+  all_genes <- all_genes[!is.na(all_genes)]
   all_terms <- result_df[, ID_column]
 
   term_genes_mat <- matrix(0,
@@ -1063,6 +1072,7 @@ term_gene_heatmap <- function(result_df, genes_df, num_terms = 10,
   for (i in seq_len(nrow(term_genes_mat))) {
     current_term <- rownames(term_genes_mat)[i]
     current_genes <- c(up_genes[[current_term]], down_genes[[current_term]])
+    current_genes <- current_genes[!is.na(current_genes)]
     term_genes_mat[i, match(current_genes, colnames(term_genes_mat))] <- 1
   }
 

tests/testthat/test-visualization_functions.R

@@ -374,6 +374,12 @@ test_that("`term_gene_heatmap()` produces a ggplot object using the correct data
   expect_is(p <- term_gene_heatmap(RA_output, num_terms = 3), "ggplot")
   expect_equal(length(unique(p$data$Enriched_Term)), 3)
 
+  # No genes in "Down_regulated"
+  res_df <- RA_output
+  res_df$Down_regulated <- ""
+  expect_is(p <- term_gene_heatmap(RA_output, num_terms = 3), "ggplot")
+  expect_equal(length(unique(p$data$Enriched_Term)), 3)
+
   # All terms
   expect_is(p <- term_gene_heatmap(RA_output, num_terms = NULL), "ggplot")
   expect_equal(length(unique(p$data$Enriched_Term)), nrow(RA_output))