test_that("clean COTAN object", {
raw <- matrix(c(1L, 0L, 4L, 2L, 11L, 0L, 6L, 7L, 0L, 9L,
10L, 8L, 0L, 0L, 0L, 3L, 0L, 0L, 2L, 0L),
nrow = 10L, ncol = 20L)
rownames(raw) <- LETTERS[1L:10L]
colnames(raw) <- letters[1L:20L]
obj <- COTAN(raw = raw)
obj <- clean(obj)
expect_true(validObject(obj))
expect_identical(colnames(getMetadataCells(obj)), c("feCells", "nu"))
expect_identical(colnames(getMetadataGenes(obj)), c("feGenes", "lambda"))
})
test_that("Clean on test dataset", {
utils::data("test.dataset", package = "COTAN")
obj <- COTAN(raw = test.dataset)
obj <- initializeMetaDataset(obj, GEO = " ",
sequencingMethod = "artificial",
sampleCondition = "test")
obj <- clean(obj)
obj <- estimateDispersionBisection(obj, cores = 6L)
raw.norm <- readRDS(file.path(getwd(), "raw.norm.test.RDS"))
lambda <- readRDS(file.path(getwd(), "lambda.test.RDS"))
dispersion <- readRDS(file.path(getwd(), "dispersion.test.RDS"))
nu <- readRDS(file.path(getwd(), "nu.test.RDS"))
genes.names.test <- readRDS(file.path(getwd(), "genes.names.test.RDS"))
cells.names.test <- readRDS(file.path(getwd(), "cells.names.test.RDS"))
expect_equal(getNuNormData(obj)[genes.names.test, cells.names.test],
raw.norm, tolerance = 1.0e-14, ignore_attr = FALSE)
expect_equal(getLambda(obj)[genes.names.test],
lambda, tolerance = 1.0e-14, ignore_attr = FALSE)
expect_equal(getNu(obj)[cells.names.test],
nu, tolerance = 1.0e-14, ignore_attr = FALSE)
expect_equal(getDispersion(obj)[genes.names.test],
dispersion, tolerance = 1.0e-14, ignore_attr = FALSE)
})
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