tests/testthat/test-gene_plot.R

In GeneTonic: Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

context("Testing function for plotting the gene expression levels")

test_that("Basic gene plot is generated", {
  p <- gene_plot(dds = dds_macrophage,
                 gene = "ENSG00000285982",
                 assay = "counts",
                 intgroup = "condition",
                 annotation_obj = anno_df,
                 transform = TRUE,
                 labels_repel = TRUE)
  expect_is(p, "gg")

  p2_noanno_normallabels_untransformed <- gene_plot(dds = dds_macrophage,
                                                    gene = "ENSG00000285982",
                                                    assay = "counts",
                                                    intgroup = "condition",
                                                    transform = FALSE,
                                                    labels_repel = FALSE)
  expect_is(p2_noanno_normallabels_untransformed, "gg")
})

test_that("Enforcing plot types", {
  p_jitter <- gene_plot(dds = dds_macrophage,
                        gene = "ENSG00000285982",
                        assay = "counts",
                        intgroup = "condition",
                        plot_type = "jitteronly")
  p_boxplot <- gene_plot(dds = dds_macrophage,
                         gene = "ENSG00000285982",
                         assay = "counts",
                         intgroup = "condition",
                         plot_type = "boxplot")
  p_violin <- gene_plot(dds = dds_macrophage,
                        gene = "ENSG00000285982",
                        assay = "counts",
                        intgroup = "condition",
                        plot_type = "violin")
  p_sina <- gene_plot(dds = dds_macrophage,
                      gene = "ENSG00000285982",
                      assay = "counts",
                      intgroup = "condition",
                      plot_type = "sina")
  expect_is(p_jitter, "gg")
  expect_is(p_boxplot, "gg")
  expect_is(p_violin, "gg")
  expect_is(p_sina, "gg")
})

test_that("Data instead of plot is returned", {
  df_jitter <- gene_plot(dds = dds_macrophage,
                         gene = "ENSG00000285982",
                         assay = "counts",
                         intgroup = "condition",
                         return_data = TRUE)
  expect_is(df_jitter, "data.frame")
})

test_that("Assays are correctly accessed", {
  p_non_norm_counts <- gene_plot(dds = dds_macrophage,
                                 gene = "ENSG00000285982",
                                 assay = "counts",
                                 intgroup = "condition",
                                 normalized = FALSE)
  expect_is(p_non_norm_counts, "gg")
  p_tpm <- gene_plot(dds = dds_macrophage,
                     gene = "ENSG00000285982",
                     assay = "abundance",
                     intgroup = "condition",
                     normalized = FALSE)
  expect_is(p_tpm, "gg")

  p_other_assay <- gene_plot(dds = dds_macrophage,
                             gene = "ENSG00000285982",
                             assay = "avgTxLength",
                             intgroup = "condition",
                             normalized = FALSE)
  expect_is(p_other_assay, "gg")
})

test_that("Extraction of expression values works", {
  df_simple <- get_expression_values(dds = dds_macrophage,
                                     gene = "ENSG00000285982",
                                     intgroup = "condition",
                                     assay = "counts")
  expect_is(df_simple, "data.frame")
  expect_error(get_expression_values(dds = dds_macrophage,
                                     gene = "ENSG00000285982",
                                     intgroup = "condition",
                                     assay = "count"))
  df_unnormalized <- get_expression_values(dds = dds_unnormalized,
                                           gene = "ENSG00000285982",
                                           intgroup = "condition",
                                           assay = "counts")
  expect_is(df_unnormalized, "data.frame")


})