Nothing
library(flowCore)
library(SingleCellExperiment)
data(sample_ff, sample_key)
data(PBMC_fs, PBMC_panel, PBMC_md)
ids <- rownames(sample_key)
test_that("sce2fcs()", {
# split by barcode population
x <- prepData(sample_ff, by_time = FALSE)
x <- assignPrelim(x, sample_key, verbose = FALSE)
expect_error(sce2fcs(x, split_by = "x"))
expect_error(sce2fcs(x, split_by = "bc_id", assay = "x"))
expect_is(sce2fcs(x, split_by = NULL), "flowFrame")
a <- sample(assayNames(x), 1)
fs <- sce2fcs(x, assay = a, split_by = "bc_id")
expect_is(fs, "flowSet")
expect_equivalent(fsApply(fs, nrow), c(table(x$bc_id)))
m <- grep(id <- sample(ids, 1), fsApply(fs, identifier))
expect_equivalent(tolerance = 1e-6,
t(exprs(fs[[m]])), assay(x, a)[, x$bc_id == id])
# missing populations
ids_ex <- sample(ids, 5)
ids_in <- setdiff(ids, ids_ex)
x <- x[, !x$bc_id %in% ids_ex]
y <- sce2fcs(x, split_by = "bc_id")
expect_equivalent(gsub(".*\\.", "", fsApply(y, identifier)), ids_in)
# split by cluster assignment
x <- prepData(PBMC_fs, PBMC_panel, PBMC_md)
x <- cluster(x, maxK = 5, verbose = FALSE)
x$cluster_id <- cluster_ids(x, "meta5")
y <- sce2fcs(x, split_by = "cluster_id")
expect_equivalent(fsApply(y, nrow), c(table(x$cluster_id)))
# with propagation of dimension reductions
x <- runDR(x, dr = "PCA", ncomponents = 2)
y <- sce2fcs(x, split_by = "sample_id", keep_dr = TRUE)
expect_true(length(y) == nlevels(x$sample_id))
expect_true(ncol(y[[1]]) == nrow(x) + ncol(reducedDim(x)))
})
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