context("rarefyAssay")
test_that("rarefyAssay", {
library(bluster)
data(GlobalPatterns, package="mia")
# Parameters validity check
expect_error(addCluster(GlobalPatterns,
KmeansParam(centers = 3),
assay.type = "error"))
# Checking wrong by (char)
expect_error(addCluster(GlobalPatterns,
KmeansParam(centers = 3),
by = "error"))
# Checking wrong by (number)
expect_error(addCluster(GlobalPatterns,
KmeansParam(centers = 3),
by = 3))
tse <- addCluster(GlobalPatterns,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE,
clust.col = "customdataname")
altExp(tse, "test") <- tse[1:1000,]
# Checking same name that is already present
expect_warning(addCluster(tse,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE))
# Checking wrong clust.col with already-present name
expect_warning(addCluster(tse,
KmeansParam(centers = 3),
clust.col = "customdataname"))
# Checking wrong altexp
expect_error(addCluster(tse,
KmeansParam(centers = 3),
altexp = "error"))
# Parameters check
tse <- GlobalPatterns
altExp(tse, "test") <- tse[1:1000,]
tse <- addCluster(tse,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE,
clust.col = "customdataname")
tse <- addCluster(tse,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE,
clust.col = "customdataname",
altexp = "test")
# Checking custom metadata/dataname in main/altExp
expect_true("custommetadata" %in% names(metadata(tse)))
expect_true("customdataname" %in% names(rowData(tse)))
expect_true("custommetadata" %in% names(metadata(altExp(tse, "test"))))
expect_true("customdataname" %in% names(rowData(altExp(tse, "test"))))
# Checking existing custom metadata/dataname in main/altExp
expect_warning(addCluster(tse,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE))
expect_warning(addCluster(tse,
KmeansParam(centers = 3),
clust.col = "customdataname"))
expect_warning(addCluster(tse,
KmeansParam(centers = 3),
name = "custommetadata",
full = TRUE,
clust.col = "customdataname",
altexp = "test"))
# Checking working by
tse <- GlobalPatterns
altExp(tse, "test") <- tse[1:1000,]
tse <- addCluster(tse,
KmeansParam(centers = 3),
by = "col")
tse <- addCluster(tse,
KmeansParam(centers = 3),
altexp = "test",
by = 2)
expect_true("clusters" %in% names(colData(tse)))
expect_true("clusters" %in% names(colData(altExp(tse, "test"))))
# Checking wrapper operational
tse <- GlobalPatterns
altExp(tse, "test") <- tse[1:2000,]
tse <- addCluster(tse,
HclustParam(),
by = "col")
tse <- addCluster(tse,
HclustParam(),
by = "row",
altexp = "test",
full = TRUE)
expectedCol <- clusterRows(t(assay(tse, "counts")), HclustParam())
expectedRow <- clusterRows(assay(altExp(tse, "test"), "counts"),
HclustParam(), full = TRUE)
# Checking same output on cols
expect_identical(expectedCol, colData(tse)$clusters)
# Checking same output on rows
expect_identical(expectedRow$clusters,
rowData(altExp(tse, "test"))$clusters)
# Checking same metdata output on rows
expect_identical(expectedRow$objects,
metadata(altExp(tse, "test"))$clusters)
})
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