Nothing
context("test-dimensional_reduction")
set.seed(seed = 1)
dummyexpMat <- matrix(
data = sample(x = c(1:50), size = 1e4, replace = TRUE),
ncol = 100, nrow = 100
)
colnames(x = dummyexpMat) <- paste0("cell", seq(ncol(x = dummyexpMat)))
row.names(x = dummyexpMat) <- paste0("gene", seq(nrow(x = dummyexpMat)))
# Create Seurat object for testing
obj <- CreateSeuratObject(counts = as.sparse(dummyexpMat))
test_that("different ways of passing distance matrix", {
# Manually make a distance object to test
distMat <- dist(t(dummyexpMat))
expect_equivalent(
suppressWarnings(expr = RunTSNE(obj, distance.matrix = distMat)),
suppressWarnings(expr = RunTSNE(obj, distance.matrix = as.matrix(distMat)))
)
expect_equivalent(
suppressWarnings(expr = RunTSNE(obj, distance.matrix = distMat)@reductions$tsne),
suppressWarnings(expr = RunTSNE(distMat, assay = "RNA"))
)
expect_equivalent(
suppressWarnings(expr = RunTSNE(obj, distance.matrix = distMat)@reductions$tsne),
suppressWarnings(expr = RunTSNE(as.matrix(distMat), assay = "RNA", is_distance = TRUE))
)
})
# Normalize, scale, and compute PCA, using RunPCA
obj <- NormalizeData(object = obj, verbose = FALSE)
obj <- ScaleData(object = obj, verbose = FALSE)
pca_result <- suppressWarnings(expr = RunPCA(
object = obj,
features = rownames(obj[['RNA']]$counts),
verbose = FALSE
))
test_that("pca returns total variance (see #982)", {
# Using stats::prcomp
scaled_data <- LayerData(object = obj, layer = "scale.data")
prcomp_result <- stats::prcomp(scaled_data, center = FALSE, scale. = FALSE)
# Compare
expect_equivalent(slot(object = pca_result[["pca"]], name = "misc")$total.variance,
sum(prcomp_result$sdev^2))
})
test_that("pca is equivalent for BPCells", {
skip_on_cran()
skip_if_not_installed("BPCells")
library(BPCells)
library(Matrix)
mat_bpcells <- t(x = as(object = t(x = obj[['RNA']]$counts ), Class = "IterableMatrix"))
obj[['RNAbp']] <- CreateAssay5Object(counts = mat_bpcells)
DefaultAssay(obj) <- "RNAbp"
obj <- NormalizeData(object = obj, verbose = FALSE)
obj <- ScaleData(object = obj, verbose=FALSE)
pca_result_bp <- suppressWarnings(expr = RunPCA(
object = obj,
features = rownames(obj[['RNAbp']]$counts),
assay = "RNAbp"))
expect_equivalent(abs(pca_result_bp[['pca']]@cell.embeddings),
abs(pca_result[['pca']]@cell.embeddings),
tolerance = 1e-5)
})
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