tests/testthat/test-DotPlot.R

In dtm2451/DittoSeq: User Friendly Single-Cell and Bulk RNA Sequencing Visualization

# Tests for dittoDotPlot function
# library(dittoSeq); library(testthat); source("setup.R"); source("test-DotPlot.R")

sce$number <- as.numeric(seq_along(colnames(sce)))
sce$number2 <- rev(sce$number)
disc <- "clusters"
disc2 <- "groups"
disc3 <- "age"
genes <- getGenes(sce)[1:5]
metas <- c("score", "score2", "score3")
cells.names <- colnames(sce)[1:40]
cells.logical <- c(rep(TRUE, 40), rep(FALSE,ncells-40))

test_that("dittoDotPlot can plot gene and meta data", {
    expect_s3_class(
        dittoDotPlot(sce, group.by = disc,
            genes),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, group.by = disc,
            metas),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, group.by = disc,
            c("score", "gene1")),
        "ggplot")
})

test_that("dittoDotPlot errors for single vars or non-numeric vars", {
    expect_error(
        dittoDotPlot(sce, group.by = disc,
            c("score")),
        "'vars' must be a vector of at least two", fixed = TRUE)
    
    expect_error(
        dittoDotPlot(sce, group.by = disc,
            c("gene1")),
        "'vars' must be a vector of at least two", fixed = TRUE)
    expect_error(
        dittoDotPlot(sce, group.by = disc,
            c("gene1", "gene2", disc)),
        "'vars' must be numeric", fixed = TRUE)
})

test_that("dittoDotPlot works with any gene adjustments", {
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            adjustment = "relative.to.max"),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            adjustment = "z-score"),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            adjustment = NULL),
        "ggplot")
})

test_that("dittoDotPlot scaling acts as expected", {
    # scaling on by default
    expect_type(
        d <- dittoDotPlot(sce, genes, disc,
            data.out = TRUE),
        "list")
    # Controlled by 'scale'
    expect_type(
        d2 <- dittoDotPlot(sce, genes, disc,
            scale = FALSE,
            data.out = TRUE),
        "list")
    
    expect_true( identical(d2$data$color, d$data$pre.scale))
    expect_false(identical(d2$data$color, d$data$color))
})

test_that("dittoDotPlot legend can be removed", {
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            legend.show = FALSE),
        "ggplot")
})

test_that("dittoDotPlot summary.fxns can be adjusted", {
    # Manual check: scale of color in 1, should have same range as size in 2.
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            summary.fxn.color = median),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            summary.fxn.size = median),
        "ggplot")
    
    expect_error(
        dittoDotPlot(sce, genes, disc,
            summary.fxn.color = function(x) x/2),
        "result is length", fixed = TRUE)
})

test_that("dittoDotPlot colors, sizes, ranges, legends are adjustable", {
    # Manual check: color = black to light grey, -3 to 3.
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            min.color = "black", max.color = "grey90",
            min = -3, max = 3),
        "ggplot")
    
    # Manual check: size = -0.25 to 1, dots LARGE
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            min.percent = -0.25, max.percent = 1,
            size = 10),
        "ggplot")
    
    # Manual check: color = 3 breaks, low, 0, high
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            min = -3, max = 3,
            legend.color.breaks = seq(-3,3,3),
            legend.color.breaks.labels = c("low", 0, "high")),
        "ggplot")
})

test_that("dittoDotPlot can be subset to show only certain cells/samples with any cells.use method", {
    expect_s3_class(
        {c1 <- dittoDotPlot(sce, genes, disc, data.out = TRUE,
            cells.use = cells.names)
        c1$p},
        "ggplot")
    expect_s3_class(
        {c2 <- dittoDotPlot(sce, genes, disc, data.out = TRUE,
            cells.use = cells.logical)
        c2$p},
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            cells.use = 1:40),
        "ggplot")
    expect_equal(c1$data,c2$data)
    # And if we remove an entire grouping...
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            cells.use = meta(disc,sce)!=0),
        "ggplot")
})

test_that("dittoDotPlot titles and theme can be adjusted", {
    ### Manual check: All titles should be adjusted.
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            main = "Gotta catch", sub = "em all",
            xlab = "Pokemon", ylab = "Pokedex #s",
            legend.size.title = "Pika",
            legend.color.title = "chu"),
        "ggplot")
    ### Manual check: plot should be boxed with grid lines
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            theme = theme_bw()),
        "ggplot")
})

test_that("dittoDotPlot y-labels can be adjusted", {
    # Manual check: Labels = 3,4,5,6
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            y.labels = 3:6),
        "ggplot")
    # Manual check: 4 at bottom
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            y.reorder = 4:1),
        "ggplot")
    # Manual check: x-labels horizontal
    expect_s3_class(
        dittoDotPlot(sce, genes, disc,
            x.labels.rotate = FALSE),
        "ggplot")
})

test_that("dittoDotPlot assay adjustment works", {
    expect_type(
        d_raw <- dittoDotPlot(sce, genes, disc, data.out = TRUE, scale = FALSE,
            assay = "counts"),
        "list")
    expect_type(
        d_log <- dittoDotPlot(sce, genes, disc, data.out = TRUE, scale = FALSE,
            assay = "logcounts"),
        "list")
    expect_true(all(
        d_raw$data$color >= d_log$data$color))
})

test_that("dittoDotPlot swap.rownames works", {
    
    swap_genes <- paste(genes, "symb", sep = "_")
    
    no_swap <- dittoDotPlot(sce, genes, disc, data.out = TRUE)
    swap <- dittoDotPlot(sce, swap_genes, disc, data.out = TRUE,
                         swap.rownames = "symbol")
    
    expect_equivalent(no_swap$data$color, swap$data$color)
    expect_equivalent(swap$data$var,
                      factor(paste(no_swap$data$var, "symb", sep = "_")))
    
    expect_s3_class(
        no_swap$p,
        "ggplot")
    expect_s3_class(
        swap$p,
        "ggplot")
})

test_that("dittoDotPlot split.by works", {
    
    swap_genes <- paste(genes, "symb", sep = "_")
    
    none <- dittoDotPlot(
        sce, genes, disc, data.out = TRUE)
    split1 <- dittoDotPlot(
        sce, genes, disc, data.out = TRUE,
        split.by = disc2)
    split2 <- dittoDotPlot(
        sce, genes, disc, data.out = TRUE,
        split.by = c(disc2,disc3))
    
    expect_equivalent(
        ncol(none$data)+2,
        ncol(split1$data)+1,
        ncol(split2$data)
        )
    
    expect_s3_class(
        split1$p,
        "ggplot")
    expect_s3_class(
        split2$p,
        "ggplot")
})

test_that("dittoDotPlot retains group factor levels and optionally drops unused ones", {
    not_factor <- dittoDotPlot(
        sce, genes, "groups", data.out = TRUE,
        split.by = disc2)
    
    sce$groups <- factor(sce$groups)
    with_gE <- dittoDotPlot(
        sce, genes, "groups", data.out = TRUE,
        split.by = disc2)
    without_gE <- dittoDotPlot(
        sce, genes, "groups", data.out = TRUE,
        split.by = disc2,
        cells.use = sce$groups!="E")
    without_gE_no_drop <- dittoDotPlot(
        sce, genes, "groups", data.out = TRUE,
        split.by = disc2,
        cells.use = sce$groups!="E",
        groupings.drop.unused = FALSE)
    
    # Plots made
    expect_s3_class(
        with_gE$p,
        "ggplot")
    expect_s3_class(
        without_gE$p,
        "ggplot")
    expect_s3_class(
        without_gE_no_drop$p,
        "ggplot")
    
    # Factor if originally factor, not if not
    expect_type(not_factor$data$grouping, "character")
    expect_type(with_gE$data$grouping, "integer")
    
    # Drop is optional
    expect_equal(
        levels(with_gE$data$grouping),
        levels(without_gE_no_drop$data$grouping))
    expect_true(
        length(levels(with_gE$data$grouping)) >
        length(levels(without_gE$data$grouping)))
})

test_that("dittoDotPlot vars.dir controls axis where vars are shown", {

    ### Manual check:
    # Both the below should put genes on the y-axis

    # On its own
    expect_s3_class(
        dittoDotPlot(
            sce, genes[1:5], "groups",
            vars.dir = "y"),
        "ggplot")

    # With faceting
    expect_s3_class(
        dittoDotPlot(
            sce, genes[1:5], "groups",
            vars.dir = "y",
            split.by = disc),
        "ggplot")
})


test_that("dittoDotPlot allows var-category grouping", {
    gene_list <- list('T'=getGenes(sce)[1:5],
                      'B'=getGenes(sce)[6:8],
                      getGenes(sce)[9])

    # On its own
    expect_s3_class(
        dittoDotPlot(
            sce, gene_list, "groups"),
        "ggplot")

    # With additional faceting
    expect_s3_class(
        dittoDotPlot(
            sce, gene_list, "groups",
            split.by = disc),
    "ggplot")
    expect_warning(
        dittoDotPlot(
            sce, gene_list, "groups",
            split.by = c(disc, disc2)),
    "The second element given to 'split.by'", fixed = TRUE)

    # Additional args:
    # Manual check:
    #   - categories.split.adjust & categories.theme.adjust are ON by default.
    #      If working, categories show outside of axes without their box.
    #   - Here, categories should appear on the y-axis, alongside genes.
    expect_s3_class(
        dittoDotPlot(
            sce, gene_list, "groups",
            vars.dir = "y"
            ),
        "ggplot")
})

test_that("dittoDotPlot allows 3-color scale", {
    # Just mid.color / mid.value set
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "white"),
        "ggplot")

    # "ryb", "rgb" or "rwb"
    ### Manual Check:
    # First has yellow in middle of legend
    # Second has near-white in middle of legend
    # Third has white in middle of legend
    # All have blue at bottom and red at top of legend
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "ryb"),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "rgb"),
        "ggplot")
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "rwb"),
        "ggplot")

    ## Edge-cases
    # No scaling.  mid defaults to 0
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "white",
            scale = FALSE),
        "ggplot")
    # No scaling, but min NA, mid defaults to halfway between calc'd min and max
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "white",
            scale = FALSE, min = NA),
        "ggplot")
    # mid too high, colors plotted between min and mid only because mid is
    #   higher than the max of the data.
    expect_s3_class(
        dittoDotPlot(sce, genes, "groups",
            mid.color = "white",
            mid = 1.5),
        "ggplot")
})