tests/testthat/test-visualization.R
In egeulgen/pathfindR: Enrichment Analysis Utilizing Active Subnetworks
## Tests for functions related to various visualization functions - Apr 2024
single_result <- example_pathfindR_output[1, ]
processed_input <- example_pathfindR_input[, c(1, 1, 2, 3)]
colnames(processed_input) <- c("old_GENE", "GENE", "CHANGE", "P_VALUE")
test_that("`visualize_terms()` -- calls the appropriate function", {
mock_vis_kegg <- mockery::mock(NULL)
mockery::stub(visualize_terms, "visualize_KEGG_diagram", mock_vis_kegg)
expect_silent(visualize_terms(result_df = single_result, input_processed = data.frame(),
is_KEGG_result = TRUE))
mockery::expect_called(mock_vis_kegg, 1)
mock_vis_term_inter <- mockery::mock(NULL)
mockery::stub(visualize_terms, "visualize_term_interactions", mock_vis_term_inter)
expect_silent(visualize_terms(result_df = single_result, is_KEGG_result = FALSE))
mockery::expect_called(mock_vis_term_inter, 1)
})
test_that("`visualize_terms()` -- argumment checks work", {
expect_error(visualize_terms(result_df = "INVALID"), "`result_df` should be a data frame")
# is_KEGG_result = TRUE
nec_cols <- "ID"
expect_error(visualize_terms(single_result[, -1], is_KEGG_result = TRUE), paste0("`result_df` should contain the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
# is_KEGG_result = FALSE
nec_cols <- c("Term_Description", "Up_regulated", "Down_regulated")
expect_error(visualize_terms(single_result[, -2], is_KEGG_result = FALSE), paste0("`result_df` should contain the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(visualize_terms(result_df = single_result, is_KEGG_result = TRUE), "`input_processed` should be specified when `is_KEGG_result = TRUE`")
expect_error(visualize_terms(result_df = single_result, is_KEGG_result = "INVALID"),
"the argument `is_KEGG_result` should be either TRUE or FALSE")
})
test_that("`visualize_term_interactions()` -- creates expected list of ggraph objects", {
skip_on_cran()
expect_is(res <- visualize_term_interactions(single_result, pin_name_path = "Biogrid"), "list")
expect_is(res[[1]], "ggraph")
tmp_res <- rbind(single_result, single_result)
tmp_res$Term_Description[2] <- "SKIP"
tmp_res$Up_regulated[2] <- "Gene1"
tmp_res$Down_regulated[2] <- ""
expect_message(res <- visualize_term_interactions(tmp_res, pin_name_path = "KEGG"),
paste0("< 2 genes, skipping visualization of ", tmp_res$Term_Description[2]))
# Non-empty non_Signif_Snw_Genes
tmp_res <- single_result
tmp_res$non_Signif_Snw_Genes <- example_pathfindR_output$Up_regulated[2]
expect_is(res <- visualize_term_interactions(tmp_res, pin_name_path = "Biogrid"), "list")
expect_is(res[[1]], "ggraph")
})
test_that("`visualize_KEGG_diagram()` -- creates expected list of ggraph objects", {
skip_on_cran()
expect_is(res <- visualize_KEGG_diagram(kegg_pw_ids = single_result$ID, input_processed = processed_input), "list")
expect_is(res[[1]], "ggraph")
constant_input <- processed_input
constant_input$CHANGE <- 1e+06
expect_is(visualize_KEGG_diagram(kegg_pw_ids = single_result$ID, input_processed = constant_input), "list")
expect_is(res[[1]], "ggraph")
})
test_that("`visualize_KEGG_diagram()` -- skips pathway if non-existent", {
skip_on_cran()
temp_res <- example_pathfindR_output[1:2, ]
temp_res$ID[2] <- "hsa12345"
expect_is(res <- visualize_KEGG_diagram(kegg_pw_ids = temp_res$ID, input_processed = processed_input), "list")
expect_is(res[[1]], "ggraph")
expect_length(expect_is, 1)
})
test_that("`visualize_KEGG_diagram()` -- argument checks work", {
expect_error(visualize_KEGG_diagram(kegg_pw_ids = list(), input_processed = processed_input),
"`kegg_pw_ids` should be a vector of KEGG IDs")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = c("X", "Y", "Z"), input_processed = processed_input),
"`kegg_pw_ids` should be a vector of valid hsa KEGG IDs")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = "abc12345", input_processed = list()),
"`input_processed` should be a data frame")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = "abc12345", input_processed = processed_input[,
-2]), paste0("`input_processed` should contain the following columns: ",
paste(dQuote(c("GENE", "CHANGE")), collapse = ", ")))
})
test_that("`color_kegg_pathway()` -- works as expected", {
skip_on_cran()
pw_id <- "hsa00010"
change_vec <- c(-2, 4, 6)
names(change_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_is(result <- color_kegg_pathway(pw_id, change_vec), "ggraph")
names(change_vec) <- rep("missing", 3)
expect_is(result <- color_kegg_pathway(pw_id, change_vec), "NULL")
})
test_that("`color_kegg_pathway()` -- exceptions are handled properly", {
change_vec <- c(-2, 4, 6)
names(change_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
scale_vals = "INVALID"), "`scale_vals` should be logical")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = list()), "`node_cols` should be a vector of colors")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = rep("red", 4)), "the length of `node_cols` should be 3")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = c("red", "#FFFFFF", "INVALID")), "`node_cols` should be a vector of valid colors")
skip_on_cran()
constant_vec <- rep(1e+06, 3)
names(constant_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_silent(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = c("red", "blue", "green")))
expect_message(color_kegg_pathway(pw_id = "hsa03040", change_vec = constant_vec,
node_cols = c("red", "blue", "green")))
expect_null(suppressWarnings(color_kegg_pathway(pw_id = "hsa03040", change_vec = NULL)))
expect_message(color_kegg_pathway(pw_id = "hsa11111", change_vec = c()))
})
test_that("`enrichment_chart()` -- produces a ggplot object with correct labels",
{
# default - top 10
expect_is(g <- enrichment_chart(example_pathfindR_output), "ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# plot_by_cluster
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, plot_by_cluster = TRUE),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# chang top_terms
expect_is(g <- enrichment_chart(example_pathfindR_output, top_terms = NULL),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
expect_is(g <- enrichment_chart(example_pathfindR_output, top_terms = 1000),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# change num_bubbles
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, num_bubbles = 30),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# change even_breaks
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, even_breaks = FALSE),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
})
test_that("`enrichment_chart()` -- argument checks work", {
necessary <- c("Term_Description", "Fold_Enrichment", "lowest_p", "Up_regulated",
"Down_regulated")
expect_error(enrichment_chart(example_pathfindR_output[, -2]), paste0("The input data frame must have the columns:\n",
paste(necessary, collapse = ", ")))
expect_error(enrichment_chart(example_pathfindR_output, plot_by_cluster = "INVALID"),
"`plot_by_cluster` must be either TRUE or FALSE")
expect_message(enrichment_chart(example_pathfindR_output, plot_by_cluster = TRUE),
"For plotting by cluster, there must a column named `Cluster` in the input data frame!")
expect_error(enrichment_chart(example_pathfindR_output, top_terms = "INVALID"),
"`top_terms` must be either numeric or NULL")
expect_error(enrichment_chart(example_pathfindR_output, top_terms = 0), "`top_terms` must be > 1")
})
test_that("`term_gene_graph()` -- produces a ggplot object using the correct data",
{
# Top 10 (default)
expect_is(p <- term_gene_graph(example_pathfindR_output), "ggplot")
expect_equal(sum(p$data$type == "term"), 10)
# Top 3
expect_is(p <- term_gene_graph(example_pathfindR_output, num_terms = 3),
"ggplot")
expect_equal(sum(p$data$type == "term"), 3)
# All terms
expect_is(p <- term_gene_graph(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
expect_equal(sum(p$data$type == "term"), 15)
# Top 1000, expect to plot top nrow(output)
expect_is(p <- term_gene_graph(example_pathfindR_output[1:15, ], num_terms = 1000),
"ggplot")
expect_equal(sum(p$data$type == "term"), 15)
# use_description = TRUE
expect_is(p <- term_gene_graph(example_pathfindR_output, use_description = TRUE),
"ggplot")
expect_equal(sum(p$data$type == "term"), 10)
# node_size = 'p_val'
expect_is(p <- term_gene_graph(example_pathfindR_output, node_size = "p_val"),
"ggplot")
expect_equal(sum(p$data$type == "term"), 10)
})
test_that("`term_gene_graph()` -- argument checks work", {
expect_error(term_gene_graph(example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` must either be numeric or NULL!")
expect_error(term_gene_graph(example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
val_node_size <- c("num_genes", "p_val")
expect_error(term_gene_graph(example_pathfindR_output, node_size = "INVALID"),
paste0("`node_size` should be one of ", paste(dQuote(val_node_size), collapse = ", ")))
expect_error(term_gene_graph(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
necessary_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_graph(wrong_df, use_description = FALSE), paste(c("All of",
paste(necessary_cols, collapse = ", "), "must be present in `results_df`!"),
collapse = " "))
ID_column <- "Term_Description"
necessary_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_graph(wrong_df, use_description = TRUE), paste(c("All of",
paste(necessary_cols, collapse = ", "), "must be present in `results_df`!"),
collapse = " "))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = list()))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = c(1, 2, 3)))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = c("red", "blue")))
})
test_that("`term_gene_heatmap()` -- produces a ggplot object using the correct data",
{
skip_on_cran()
# Top 10 (default)
expect_is(p <- term_gene_heatmap(example_pathfindR_output), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 10)
expect_true(all(p$data$Enriched_Term %in% example_pathfindR_output$ID))
# Top 3
expect_is(p <- term_gene_heatmap(example_pathfindR_output, num_terms = 3),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# No genes in 'Down_regulated'
res_df <- example_pathfindR_output[1:3, ]
res_df$Down_regulated <- ""
expect_is(p <- term_gene_heatmap(res_df), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# No genes in 'Up_regulated'
res_df <- example_pathfindR_output[1:3, ]
res_df$Up_regulated <- ""
expect_is(p <- term_gene_heatmap(res_df), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# All terms
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 15)
# Top 1000, expect to plot top nrow(output)
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:15, ], num_terms = 1000),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 15)
# use_description = TRUE
expect_is(p <- term_gene_heatmap(example_pathfindR_output, use_description = TRUE),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 10)
expect_true(all(p$data$Enriched_Term %in% example_pathfindR_output$Term_Description))
# genes_df supplied
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input),
"ggplot")
# genes_df supplied - wihout change column
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input[,
-2]), "ggplot")
# sort by lowest_p instead
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input,
sort_terms_by_p = TRUE), "ggplot")
})
test_that("`term_gene_graph()` -- argument checks work", {
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
expect_error(term_gene_heatmap(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_heatmap(wrong_df, use_description = FALSE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
ID_column <- "Term_Description"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_heatmap(wrong_df, use_description = TRUE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, genes_df = "INVALID"))
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` should be numeric or NULL")
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, num_terms = -1),
"`num_terms` should be > 0 or NULL")
expect_error(term_gene_heatmap(example_pathfindR_output, low = ""))
expect_error(term_gene_heatmap(example_pathfindR_output, mid = ""))
expect_error(term_gene_heatmap(example_pathfindR_output, high = ""))
})
test_that("`UpSet_plot()` -- produces a ggplot object", {
skip_on_cran()
# Top 10 (default)
expect_is(p <- UpSet_plot(example_pathfindR_output), "ggplot")
# Top 3
expect_is(p <- UpSet_plot(example_pathfindR_output, num_terms = 3), "ggplot")
# All terms
expect_is(p <- UpSet_plot(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
# No genes in 'Down_regulated'
res_df <- example_pathfindR_output
res_df$Down_regulated <- ""
expect_is(p <- UpSet_plot(res_df, num_terms = 3), "ggplot")
# No genes in 'Up_regulated'
res_df <- example_pathfindR_output
res_df$Up_regulated <- ""
expect_is(p <- UpSet_plot(res_df, num_terms = 3), "ggplot")
# use_description = TRUE
expect_is(p <- UpSet_plot(example_pathfindR_output, use_description = TRUE),
"ggplot")
# Other visualization types
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], example_pathfindR_input[1:10,
]), "ggplot")
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], example_pathfindR_input[1:10,
], method = "boxplot"), "ggplot")
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], method = "barplot"),
"ggplot")
})
test_that("`UpSet_plot()` -- argument checks work", {
expect_error(UpSet_plot(result_df = example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
expect_error(UpSet_plot(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(UpSet_plot(wrong_df, use_description = FALSE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
ID_column <- "Term_Description"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(UpSet_plot(wrong_df, use_description = TRUE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(UpSet_plot(result_df = example_pathfindR_output, genes_df = "INVALID"))
expect_error(UpSet_plot(result_df = example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` should be numeric or NULL")
expect_error(UpSet_plot(result_df = example_pathfindR_output, num_terms = -1),
"`num_terms` should be > 0 or NULL")
valid_opts <- c("heatmap", "boxplot", "barplot")
expect_error(UpSet_plot(result_df = example_pathfindR_output, method = "INVALID"),
paste("`method` should be one of`", paste(dQuote(valid_opts), collapse = ", ")))
expect_error(UpSet_plot(result_df = example_pathfindR_output, method = "boxplot"),
"For `method = boxplot`, you must provide `genes_df`")
expect_error(UpSet_plot(example_pathfindR_output, low = ""))
expect_error(UpSet_plot(example_pathfindR_output, mid = ""))
expect_error(UpSet_plot(example_pathfindR_output, high = ""))
})
test_that("`isColor()` -- identifies colors correctly", {
expect_true(isColor("red"))
expect_true(isColor("green"))
expect_true(isColor("black"))
expect_true(isColor("gray60"))
expect_true(isColor("#E5D7BF"))
expect_false(isColor(""))
expect_false(isColor("a"))
expect_false(isColor(FALSE))
expect_false(isColor(1))
expect_false(isColor(c()))
expect_false(isColor(list()))
})
egeulgen/pathfindR documentation built on May 8, 2024, 8:40 a.m.
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## Tests for functions related to various visualization functions - Apr 2024
single_result <- example_pathfindR_output[1, ]
processed_input <- example_pathfindR_input[, c(1, 1, 2, 3)]
colnames(processed_input) <- c("old_GENE", "GENE", "CHANGE", "P_VALUE")
test_that("`visualize_terms()` -- calls the appropriate function", {
mock_vis_kegg <- mockery::mock(NULL)
mockery::stub(visualize_terms, "visualize_KEGG_diagram", mock_vis_kegg)
expect_silent(visualize_terms(result_df = single_result, input_processed = data.frame(),
is_KEGG_result = TRUE))
mockery::expect_called(mock_vis_kegg, 1)
mock_vis_term_inter <- mockery::mock(NULL)
mockery::stub(visualize_terms, "visualize_term_interactions", mock_vis_term_inter)
expect_silent(visualize_terms(result_df = single_result, is_KEGG_result = FALSE))
mockery::expect_called(mock_vis_term_inter, 1)
})
test_that("`visualize_terms()` -- argumment checks work", {
expect_error(visualize_terms(result_df = "INVALID"), "`result_df` should be a data frame")
# is_KEGG_result = TRUE
nec_cols <- "ID"
expect_error(visualize_terms(single_result[, -1], is_KEGG_result = TRUE), paste0("`result_df` should contain the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
# is_KEGG_result = FALSE
nec_cols <- c("Term_Description", "Up_regulated", "Down_regulated")
expect_error(visualize_terms(single_result[, -2], is_KEGG_result = FALSE), paste0("`result_df` should contain the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(visualize_terms(result_df = single_result, is_KEGG_result = TRUE), "`input_processed` should be specified when `is_KEGG_result = TRUE`")
expect_error(visualize_terms(result_df = single_result, is_KEGG_result = "INVALID"),
"the argument `is_KEGG_result` should be either TRUE or FALSE")
})
test_that("`visualize_term_interactions()` -- creates expected list of ggraph objects", {
skip_on_cran()
expect_is(res <- visualize_term_interactions(single_result, pin_name_path = "Biogrid"), "list")
expect_is(res[[1]], "ggraph")
tmp_res <- rbind(single_result, single_result)
tmp_res$Term_Description[2] <- "SKIP"
tmp_res$Up_regulated[2] <- "Gene1"
tmp_res$Down_regulated[2] <- ""
expect_message(res <- visualize_term_interactions(tmp_res, pin_name_path = "KEGG"),
paste0("< 2 genes, skipping visualization of ", tmp_res$Term_Description[2]))
# Non-empty non_Signif_Snw_Genes
tmp_res <- single_result
tmp_res$non_Signif_Snw_Genes <- example_pathfindR_output$Up_regulated[2]
expect_is(res <- visualize_term_interactions(tmp_res, pin_name_path = "Biogrid"), "list")
expect_is(res[[1]], "ggraph")
})
test_that("`visualize_KEGG_diagram()` -- creates expected list of ggraph objects", {
skip_on_cran()
expect_is(res <- visualize_KEGG_diagram(kegg_pw_ids = single_result$ID, input_processed = processed_input), "list")
expect_is(res[[1]], "ggraph")
constant_input <- processed_input
constant_input$CHANGE <- 1e+06
expect_is(visualize_KEGG_diagram(kegg_pw_ids = single_result$ID, input_processed = constant_input), "list")
expect_is(res[[1]], "ggraph")
})
test_that("`visualize_KEGG_diagram()` -- skips pathway if non-existent", {
skip_on_cran()
temp_res <- example_pathfindR_output[1:2, ]
temp_res$ID[2] <- "hsa12345"
expect_is(res <- visualize_KEGG_diagram(kegg_pw_ids = temp_res$ID, input_processed = processed_input), "list")
expect_is(res[[1]], "ggraph")
expect_length(expect_is, 1)
})
test_that("`visualize_KEGG_diagram()` -- argument checks work", {
expect_error(visualize_KEGG_diagram(kegg_pw_ids = list(), input_processed = processed_input),
"`kegg_pw_ids` should be a vector of KEGG IDs")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = c("X", "Y", "Z"), input_processed = processed_input),
"`kegg_pw_ids` should be a vector of valid hsa KEGG IDs")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = "abc12345", input_processed = list()),
"`input_processed` should be a data frame")
expect_error(visualize_KEGG_diagram(kegg_pw_ids = "abc12345", input_processed = processed_input[,
-2]), paste0("`input_processed` should contain the following columns: ",
paste(dQuote(c("GENE", "CHANGE")), collapse = ", ")))
})
test_that("`color_kegg_pathway()` -- works as expected", {
skip_on_cran()
pw_id <- "hsa00010"
change_vec <- c(-2, 4, 6)
names(change_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_is(result <- color_kegg_pathway(pw_id, change_vec), "ggraph")
names(change_vec) <- rep("missing", 3)
expect_is(result <- color_kegg_pathway(pw_id, change_vec), "NULL")
})
test_that("`color_kegg_pathway()` -- exceptions are handled properly", {
change_vec <- c(-2, 4, 6)
names(change_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
scale_vals = "INVALID"), "`scale_vals` should be logical")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = list()), "`node_cols` should be a vector of colors")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = rep("red", 4)), "the length of `node_cols` should be 3")
expect_error(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = c("red", "#FFFFFF", "INVALID")), "`node_cols` should be a vector of valid colors")
skip_on_cran()
constant_vec <- rep(1e+06, 3)
names(constant_vec) <- c("hsa:2821", "hsa:226", "hsa:229")
expect_silent(color_kegg_pathway(pw_id = "hsa03040", change_vec = change_vec,
node_cols = c("red", "blue", "green")))
expect_message(color_kegg_pathway(pw_id = "hsa03040", change_vec = constant_vec,
node_cols = c("red", "blue", "green")))
expect_null(suppressWarnings(color_kegg_pathway(pw_id = "hsa03040", change_vec = NULL)))
expect_message(color_kegg_pathway(pw_id = "hsa11111", change_vec = c()))
})
test_that("`enrichment_chart()` -- produces a ggplot object with correct labels",
{
# default - top 10
expect_is(g <- enrichment_chart(example_pathfindR_output), "ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# plot_by_cluster
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, plot_by_cluster = TRUE),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# chang top_terms
expect_is(g <- enrichment_chart(example_pathfindR_output, top_terms = NULL),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
expect_is(g <- enrichment_chart(example_pathfindR_output, top_terms = 1000),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# change num_bubbles
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, num_bubbles = 30),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
# change even_breaks
expect_is(g <- enrichment_chart(example_pathfindR_output_clustered, even_breaks = FALSE),
"ggplot")
expect_equal(ggplot2::quo_name(g$mapping$x), "Fold_Enrichment")
expect_equal(ggplot2::quo_name(g$mapping$y), "Term_Description")
expect_equal(g$labels$size, "# genes")
expect_equal(g$labels$colour, expression(-log[10](p)))
expect_equal(g$labels$x, "Fold Enrichment")
expect_equal(g$labels$y, "Term_Description")
})
test_that("`enrichment_chart()` -- argument checks work", {
necessary <- c("Term_Description", "Fold_Enrichment", "lowest_p", "Up_regulated",
"Down_regulated")
expect_error(enrichment_chart(example_pathfindR_output[, -2]), paste0("The input data frame must have the columns:\n",
paste(necessary, collapse = ", ")))
expect_error(enrichment_chart(example_pathfindR_output, plot_by_cluster = "INVALID"),
"`plot_by_cluster` must be either TRUE or FALSE")
expect_message(enrichment_chart(example_pathfindR_output, plot_by_cluster = TRUE),
"For plotting by cluster, there must a column named `Cluster` in the input data frame!")
expect_error(enrichment_chart(example_pathfindR_output, top_terms = "INVALID"),
"`top_terms` must be either numeric or NULL")
expect_error(enrichment_chart(example_pathfindR_output, top_terms = 0), "`top_terms` must be > 1")
})
test_that("`term_gene_graph()` -- produces a ggplot object using the correct data",
{
# Top 10 (default)
expect_is(p <- term_gene_graph(example_pathfindR_output), "ggplot")
expect_equal(sum(p$data$type == "term"), 10)
# Top 3
expect_is(p <- term_gene_graph(example_pathfindR_output, num_terms = 3),
"ggplot")
expect_equal(sum(p$data$type == "term"), 3)
# All terms
expect_is(p <- term_gene_graph(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
expect_equal(sum(p$data$type == "term"), 15)
# Top 1000, expect to plot top nrow(output)
expect_is(p <- term_gene_graph(example_pathfindR_output[1:15, ], num_terms = 1000),
"ggplot")
expect_equal(sum(p$data$type == "term"), 15)
# use_description = TRUE
expect_is(p <- term_gene_graph(example_pathfindR_output, use_description = TRUE),
"ggplot")
expect_equal(sum(p$data$type == "term"), 10)
# node_size = 'p_val'
expect_is(p <- term_gene_graph(example_pathfindR_output, node_size = "p_val"),
"ggplot")
expect_equal(sum(p$data$type == "term"), 10)
})
test_that("`term_gene_graph()` -- argument checks work", {
expect_error(term_gene_graph(example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` must either be numeric or NULL!")
expect_error(term_gene_graph(example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
val_node_size <- c("num_genes", "p_val")
expect_error(term_gene_graph(example_pathfindR_output, node_size = "INVALID"),
paste0("`node_size` should be one of ", paste(dQuote(val_node_size), collapse = ", ")))
expect_error(term_gene_graph(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
necessary_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_graph(wrong_df, use_description = FALSE), paste(c("All of",
paste(necessary_cols, collapse = ", "), "must be present in `results_df`!"),
collapse = " "))
ID_column <- "Term_Description"
necessary_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_graph(wrong_df, use_description = TRUE), paste(c("All of",
paste(necessary_cols, collapse = ", "), "must be present in `results_df`!"),
collapse = " "))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = list()))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = c(1, 2, 3)))
expect_error(term_gene_graph(example_pathfindR_output, node_colors = c("red", "blue")))
})
test_that("`term_gene_heatmap()` -- produces a ggplot object using the correct data",
{
skip_on_cran()
# Top 10 (default)
expect_is(p <- term_gene_heatmap(example_pathfindR_output), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 10)
expect_true(all(p$data$Enriched_Term %in% example_pathfindR_output$ID))
# Top 3
expect_is(p <- term_gene_heatmap(example_pathfindR_output, num_terms = 3),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# No genes in 'Down_regulated'
res_df <- example_pathfindR_output[1:3, ]
res_df$Down_regulated <- ""
expect_is(p <- term_gene_heatmap(res_df), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# No genes in 'Up_regulated'
res_df <- example_pathfindR_output[1:3, ]
res_df$Up_regulated <- ""
expect_is(p <- term_gene_heatmap(res_df), "ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 3)
# All terms
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 15)
# Top 1000, expect to plot top nrow(output)
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:15, ], num_terms = 1000),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 15)
# use_description = TRUE
expect_is(p <- term_gene_heatmap(example_pathfindR_output, use_description = TRUE),
"ggplot")
expect_equal(length(unique(p$data$Enriched_Term)), 10)
expect_true(all(p$data$Enriched_Term %in% example_pathfindR_output$Term_Description))
# genes_df supplied
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input),
"ggplot")
# genes_df supplied - wihout change column
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input[,
-2]), "ggplot")
# sort by lowest_p instead
expect_is(p <- term_gene_heatmap(example_pathfindR_output[1:3, ], example_pathfindR_input,
sort_terms_by_p = TRUE), "ggplot")
})
test_that("`term_gene_graph()` -- argument checks work", {
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
expect_error(term_gene_heatmap(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_heatmap(wrong_df, use_description = FALSE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
ID_column <- "Term_Description"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(term_gene_heatmap(wrong_df, use_description = TRUE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, genes_df = "INVALID"))
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` should be numeric or NULL")
expect_error(term_gene_heatmap(result_df = example_pathfindR_output, num_terms = -1),
"`num_terms` should be > 0 or NULL")
expect_error(term_gene_heatmap(example_pathfindR_output, low = ""))
expect_error(term_gene_heatmap(example_pathfindR_output, mid = ""))
expect_error(term_gene_heatmap(example_pathfindR_output, high = ""))
})
test_that("`UpSet_plot()` -- produces a ggplot object", {
skip_on_cran()
# Top 10 (default)
expect_is(p <- UpSet_plot(example_pathfindR_output), "ggplot")
# Top 3
expect_is(p <- UpSet_plot(example_pathfindR_output, num_terms = 3), "ggplot")
# All terms
expect_is(p <- UpSet_plot(example_pathfindR_output[1:15, ], num_terms = NULL),
"ggplot")
# No genes in 'Down_regulated'
res_df <- example_pathfindR_output
res_df$Down_regulated <- ""
expect_is(p <- UpSet_plot(res_df, num_terms = 3), "ggplot")
# No genes in 'Up_regulated'
res_df <- example_pathfindR_output
res_df$Up_regulated <- ""
expect_is(p <- UpSet_plot(res_df, num_terms = 3), "ggplot")
# use_description = TRUE
expect_is(p <- UpSet_plot(example_pathfindR_output, use_description = TRUE),
"ggplot")
# Other visualization types
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], example_pathfindR_input[1:10,
]), "ggplot")
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], example_pathfindR_input[1:10,
], method = "boxplot"), "ggplot")
expect_is(p <- UpSet_plot(example_pathfindR_output[1:3, ], method = "barplot"),
"ggplot")
})
test_that("`UpSet_plot()` -- argument checks work", {
expect_error(UpSet_plot(result_df = example_pathfindR_output, use_description = "INVALID"),
"`use_description` must either be TRUE or FALSE!")
expect_error(UpSet_plot(result_df = "INVALID"), "`result_df` should be a data frame")
wrong_df <- example_pathfindR_output[, -c(1, 2)]
ID_column <- "ID"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(UpSet_plot(wrong_df, use_description = FALSE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
ID_column <- "Term_Description"
nec_cols <- c(ID_column, "lowest_p", "Up_regulated", "Down_regulated")
expect_error(UpSet_plot(wrong_df, use_description = TRUE), paste0("`result_df` should have the following columns: ",
paste(dQuote(nec_cols), collapse = ", ")))
expect_error(UpSet_plot(result_df = example_pathfindR_output, genes_df = "INVALID"))
expect_error(UpSet_plot(result_df = example_pathfindR_output, num_terms = "INVALID"),
"`num_terms` should be numeric or NULL")
expect_error(UpSet_plot(result_df = example_pathfindR_output, num_terms = -1),
"`num_terms` should be > 0 or NULL")
valid_opts <- c("heatmap", "boxplot", "barplot")
expect_error(UpSet_plot(result_df = example_pathfindR_output, method = "INVALID"),
paste("`method` should be one of`", paste(dQuote(valid_opts), collapse = ", ")))
expect_error(UpSet_plot(result_df = example_pathfindR_output, method = "boxplot"),
"For `method = boxplot`, you must provide `genes_df`")
expect_error(UpSet_plot(example_pathfindR_output, low = ""))
expect_error(UpSet_plot(example_pathfindR_output, mid = ""))
expect_error(UpSet_plot(example_pathfindR_output, high = ""))
})
test_that("`isColor()` -- identifies colors correctly", {
expect_true(isColor("red"))
expect_true(isColor("green"))
expect_true(isColor("black"))
expect_true(isColor("gray60"))
expect_true(isColor("#E5D7BF"))
expect_false(isColor(""))
expect_false(isColor("a"))
expect_false(isColor(FALSE))
expect_false(isColor(1))
expect_false(isColor(c()))
expect_false(isColor(list()))
})
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