context("netSmooth")
require(Matrix)
data("smallPPI")
data("smallscRNAseq")
test_that("netSmooth accepts SingleCellExperiment", {
sink(ifelse(.Platform$OS.type=='unix', '/dev/null', 'NUL'))
netSmooth(smallscRNAseq, smallPPI, alpha=.5)
sink()
})
test_that("netSmooth accepts sparse matrices", {
sink(ifelse(.Platform$OS.type=='unix', '/dev/null', 'NUL'))
netSmooth(Matrix(assay(smallscRNAseq)), smallPPI, alpha=.5)
netSmooth(Matrix(assay(smallscRNAseq)), smallPPI, alpha='auto', autoAlphaMethod='entropy')
sink()
})
test_that("stops with error message if PPI has zero rows/columns", {
smallPPI.with.zero.row <- data.table::copy(smallPPI)
smallPPI.with.zero.row[10,] <- 0
smallPPI.with.zero.row[,10] <- 0
expect_error(netSmooth(smallscRNAseq, smallPPI.with.zero.row, 0.5))
})
test_that("pickDimReduction is usable with umap", {
sink(ifelse(.Platform$OS.type=='unix', '/dev/null', 'NUL'))
expect_equal(pickDimReduction((assay(smallscRNAseq)),
flavors='umap',
is.counts=TRUE),
"umap")
sink()
})
test_that("robusClusters work with umap", {
sink(ifelse(.Platform$OS.type=='unix', '/dev/null', 'NUL'))
expect_is(robustClusters(smallscRNAseq,
makeConsensusMinSize=2,
makeConsensusProportion=.9,
dimReduceFlavor = 'umap'),
"list")
sink()
})
test_that("netSmooth accepts DelayedMatrix objects", {
sink(ifelse(.Platform$OS.type=='unix', '/dev/null', 'NUL'))
singleHDF5 <- as(assay(smallscRNAseq), "HDF5Array")
rownames(singleHDF5) <- rownames(smallscRNAseq)
colnames(singleHDF5) <- colnames(smallscRNAseq)
netSmooth(singleHDF5, smallPPI, alpha=.5)
netSmooth(singleHDF5, smallPPI, alpha='auto', autoAlphaMethod='entropy')
sink()
})
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