# Tests for dittoDimPlot function
# library(dittoSeq); library(testthat); source("setup.R"); source("test-DimPlot-SE.R")
gene <- "gene1"
cont <- "score2"
disc <- "groups"
disc2 <- "age"
cells.names <- colnames(sce)[1:40]
cells.logical <- c(rep(TRUE, 40), rep(FALSE,ncells-40))
cols <- c("red", "blue", "yellow", "green", "black", "gray", "white")
se <- as(sce, 'SummarizedExperiment')
rownames(se) <- rownames(sce)
embeds <- reducedDim(sce, 'PCA')
test_that("dittoDimPlot can plot continuous or discrete data & raw or normalized expression, for SEs", {
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds),
"ggplot")
expect_s3_class(
dittoDimPlot(
cont, object = se, reduction.use = embeds),
"ggplot")
expect_s3_class(
dittoDimPlot(
gene, object = se, reduction.use = embeds),
"ggplot")
expect_s3_class(
dittoDimPlot(
gene, object = se, reduction.use = embeds,
assay = "counts"),
"ggplot")
})
test_that("dittoDimPlots can be subset to show only certain cells/samples with any cells.use method, for SEs", {
expect_s3_class(
{c1 <- dittoDimPlot(
disc, object = se, reduction.use = embeds, data.out = TRUE,
cells.use = cells.names)
c1$p},
"ggplot")
expect_s3_class(
{c2 <- dittoDimPlot(
disc, object = se, reduction.use = embeds, data.out = TRUE,
cells.use = cells.logical)
c2$p},
"ggplot")
c3 <- dittoDimPlot(
disc, object = se, reduction.use = embeds,
cells.use = 1:40,
data.out = TRUE)
expect_equal(c1$Target_data, c2$Target_data)
expect_equal(c1$Target_data, c3$Target_data)
expect_equal(nrow(c3$Target_data), 40)
# And if we remove an entire grouping...
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
cells.use = meta(disc,sce)!="A"),
"ggplot")
})
test_that("dittoDimPlot reduction.use dims can be changed, for SEs", {
### Manuel Check: these should look obviously distinct
expect_s3_class(
dittoDimPlot(
cont, object = se, reduction.use = embeds),
"ggplot")
expect_s3_class(
dittoDimPlot(
cont, object = se, reduction.use = embeds,
dim.1 = 3, dim.2 = 5),
"ggplot")
})
test_that("dittoDimPlots discrete labels can be adjusted", {
# Manual Check: 5:9
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
rename.var.groups = 5:9),
"ggplot")
# Manual Check: 3:6
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
shape.by = disc2, rename.shape.groups = 3:6),
"ggplot")
})
test_that("dittoDimPlot can be labeled or circled", {
### Manual Check: Labels should repel in the first two (and move between
# plots), and 1&3 with background, 2&4 without, 5: smaller labels
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.label = TRUE),
"ggplot")
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.label = TRUE,
labels.highlight = FALSE),
"ggplot")
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.label = TRUE,
labels.repel = FALSE),
"ggplot")
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.label = TRUE,
labels.highlight = FALSE,
labels.repel = FALSE),
"ggplot")
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.label = TRUE,
labels.size = 3),
"ggplot")
})
test_that("dittoDimPlot trajectory adding works", {
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
add.trajectory.lineages = list(
c("B","A","C"),
c("C","A")),
trajectory.cluster.meta = disc,
do.label = TRUE),
"ggplot")
# Manual Check: Arrows should move & GROW.
expect_s3_class(
dittoDimPlot(
cont, object = se, reduction.use = embeds,
add.trajectory.lineages = list(
c("C","A")),
trajectory.cluster.meta = disc,
trajectory.arrow.size = 1),
"ggplot")
# Manual Check: Arrows should be detached from points
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
add.trajectory.curves = list(
data.frame(
c(-10,0,-20),
c(-20,-10,0)),
data.frame(
c(5:20),
c(5:10,9:5,6:10)
)),
trajectory.cluster.meta = disc),
"ggplot")
})
test_that("dittoDimPlot lettering works", {
### Manual Check: Letters should be added
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.letter = TRUE, size = 3),
"ggplot")
### Manual Check: see through dots and letters
expect_s3_class(
dittoDimPlot(
disc, object = se, reduction.use = embeds,
do.letter = TRUE, size = 3,
opacity = 0.5),
"ggplot")
})
test_that("dittoDimPlot can add extra vars to dataframe", {
df1 <- dittoDimPlot(
disc, object = se, reduction.use = embeds,
data.out = TRUE)[[2]]
expect_s3_class(
df2 <- dittoDimPlot(
disc, object = se, reduction.use = embeds,
extra.vars = c(gene, disc2), data.out = TRUE)[[2]],
"data.frame")
expect_equal(ncol(df1), 3)
expect_equal(ncol(df2), 5)
})
test_that("dittoDimPlot genes can be different data types", {
df <- dittoDimPlot(gene, object = se, reduction.use = embeds, data.out = TRUE,
assay = "counts")
expect_equal(
df$Target_data$color,
round(df$Target_data$color,0))
df <- dittoDimPlot(gene, object = se, reduction.use = embeds, data.out = TRUE,
adjustment = "relative.to.max")
expect_equal(
0:1,
range(df$Target_data$color))
})
test_that("dittoDimPlot adding contours", {
expect_s3_class(dittoDimPlot(object = se, reduction.use = embeds, disc,
do.contour = TRUE),
"ggplot")
### Manual Check: Contour lines light blue and dashed
expect_s3_class(dittoDimPlot(object = se, reduction.use = embeds, disc,
do.contour = TRUE,
contour.color = "lightblue", contour.linetype = "dashed"),
"ggplot")
})
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