tests/testthat/test_dataset.R

In omnideconv/SimBu: Simulate Bulk RNA-seq Datasets from Single-Cell Datasets

library(Matrix)
library(SummarizedExperiment)

counts <- Matrix::Matrix(matrix(rpois(3e5, 5), ncol = 300), sparse = TRUE)
tpm <- Matrix::Matrix(matrix(rpois(3e5, 5), ncol = 300), sparse = TRUE)
tpm <- Matrix::t(1e6 * Matrix::t(tpm) / Matrix::colSums(tpm))

colnames(counts) <- paste0("cell_", rep(1:300))
colnames(tpm) <- paste0("cell_", rep(1:300))
rownames(counts) <- paste0("gene-", rep(1:1000))
rownames(tpm) <- paste0("gene-", rep(1:1000))

test_that("can create dataset with counts or counts+tpm", {
  annotation <- data.frame(
    "ID" = paste0("cell_", rep(1:300)),
    "cell_type" = c(rep("T cells CD4", 300))
  )

  testthat::expect_s4_class(SimBu::dataset(annotation = annotation, count_matrix = counts, tpm_matrix = tpm, name = "test_dataset"), "SummarizedExperiment")
  testthat::expect_s4_class(SimBu::dataset(annotation = annotation, count_matrix = counts, name = "test_dataset"), "SummarizedExperiment")
  testthat::expect_error(SimBu::dataset(annotation = annotation, tpm_matrix = tpm, name = "test_dataset"))
})


test_that("carry over additional columns from annotation + have nReads_SimBu and nGenes_SimBu in anno", {
  annotation <- data.frame(
    "ID" = paste0("cell_", rep(1:300)),
    "cell_type" = c(rep("T cells CD4", 300)),
    "spikes" = runif(300),
    "add_1" = runif(300),
    "add_2" = runif(300)
  )

  ds <- SimBu::dataset(
    annotation = annotation,
    count_matrix = counts,
    name = "test_dataset",
    spike_in_col = "spikes",
    additional_cols = c("add_1", "add_2")
  )

  anno_ds <- data.frame(SummarizedExperiment::colData(ds))

  testthat::expect_true(all(c("add_1", "add_2") %in% colnames(anno_ds)))
  testthat::expect_true("spike_in" %in% colnames(anno_ds))
  testthat::expect_true("nReads_SimBu" %in% colnames(anno_ds))
  testthat::expect_true("nGenes_SimBu" %in% colnames(anno_ds))
})

test_that("can create dataset from seurat object", {
  annotation <- data.frame(
    "ID" = paste0("cell_", rep(1:300)),
    "cell_type" = c(
      rep("T cells CD4", 50),
      rep("T cells CD8", 50),
      rep("Macrophages", 100),
      rep("NK cells", 10),
      rep("B cells", 70),
      rep("Monocytes", 20)
    ),
    row.names = paste0("cell_", rep(1:300))
  )

  seurat_obj <- Seurat::CreateSeuratObject(counts = counts, assay = "gene_expression", meta.data = annotation)
  # store normalized matrix in the 'data' layer
  SeuratObject::LayerData(seurat_obj, assay = "gene_expression", layer = "data") <- tpm

  testthat::expect_s4_class(SimBu::dataset_seurat(seurat_obj = seurat_obj, counts_layer = "counts", cell_id_col = "ID", cell_type_col = "cell_type", tpm_layer = "data", name = "seurat_dataset"), "SummarizedExperiment")
  testthat::expect_s4_class(SimBu::dataset_seurat(seurat_obj = seurat_obj, counts_layer = "counts", cell_id_col = "ID", cell_type_col = "cell_type", name = "seurat_dataset"), "SummarizedExperiment")
})


# test_that("can load h5ad file with cells in obs and var", {
#   h5 <- system.file("extdata", "anndata.h5ad", package = "SimBu")
#   h5_rev <- system.file("extdata", "anndata_rev.h5ad", package = "SimBu")
#
#   testthat::expect_s4_class(SimBu::dataset_h5ad(h5ad_file_counts = h5, name = "h5ad_dataset", cell_id_col = "id", cell_type_col = "group", cells_in_obs = TRUE), "SummarizedExperiment")
#   testthat::expect_s4_class(SimBu::dataset_h5ad(h5ad_file_counts = h5_rev, name = "h5ad_dataset", cell_id_col = "id", cell_type_col = "group", cells_in_obs = FALSE), "SummarizedExperiment")
# })


# test_that('check sfaira connection', {
#   setup_list <- SimBu::setup_sfaira(tempdir())
#   testthat::expect_s4_class(SimBu::dataset_sfaira(sfaira_id = 'homosapiens_lungparenchyma_2019_10x3v2_madissoon_001_10.1186/s13059-019-1906-x',sfaira_setup = setup_list, name = "test_dataset"), 'SummarizedExperiment')
# })