tests/testthat/test-visualization.R

In almeidasilvaf/cogeqc: Systematic quality checks on comparative genomics analyses

#----Load data------------------------------------------------------------------
data(tree)
data(og)
dir <- system.file("extdata", package = "cogeqc")
stats_list <- read_orthofinder_stats(dir)


#----Start tests----------------------------------------------------------------
test_that("plot_species_tree() returns a ggplot object with a species tree", {
    p <- plot_species_tree(tree)
    expect_true("ggplot" %in% class(p))
})

test_that("plot_genes_in_ogs() returns a ggplot object", {
    p <- plot_genes_in_ogs(stats_list)
    expect_true("ggplot" %in% class(p))
})

test_that("plot_species_specific_ogs() returns a ggplot object", {
    p <- plot_species_specific_ogs(stats_list)
    expect_true("ggplot" %in% class(p))
})

test_that("plot_duplications() returns a ggplot object", {
    p <- plot_duplications(stats_list)
    expect_true("ggplot" %in% class(p))
})

test_that("plot_orthofinder_stats() returns a ggplot object", {
    p <- plot_orthofinder_stats(tree, stats_list)
    expect_true("ggplot" %in% class(p))
    expect_error(plot_orthofinder_stats())
})

test_that("plot_og_overlap() returns a ggplot object", {
    p <- plot_og_overlap(stats_list)
    expect_true("ggplot" %in% class(p))
})

test_that("plot_og_sizes() returns a ggplot object", {
    p <- plot_og_sizes(og, log = TRUE)
    p2 <- plot_og_sizes(og, log = FALSE, max_size = 100)

    # Create fake orthogroup data frame with >20 species for testing
    og_sim <- data.frame(
        Orthogroup = paste0("OG", 0001:0005),
        Species = rep(paste0("sp", 1:25), 5),
        Gene = c(
            rep("gene1", 50), rep("gene2", 50),
            rep("gene3", 25)
        )
    )
    p3 <- plot_og_sizes(og_sim)

    expect_true("ggplot" %in% class(p))
    expect_true("ggplot" %in% class(p2))
    expect_true("ggplot" %in% class(p3))

})

test_that("plot_genome_stats() returns a plot composition", {

    ncbi_stats <- get_genome_stats(taxon = "Zea mays")
    user_stats <- data.frame(
        accession = "my_lovely_maize",
        sequence_length = 2.4 * 1e9,
        gene_count_total = 50000,
        CC_ratio = 1
    )

    p1 <- plot_genome_stats(ncbi_stats)
    p2 <- plot_genome_stats(ncbi_stats, user_stats)

    expect_true("ggplot" %in% class(p1))
    expect_true("ggplot" %in% class(p2))



})