## AUCell_buildRankings()
##
# Input:
# Output:
test_AUCell_buildRankings <- function()
{
library(AUCell)
##################################################
### Fake dataset
set.seed(123)
exprMatrix <- matrix(data=sample(c(rep(0, 5000), sample(1:3, 5000, replace=TRUE))),
nrow=20)
rownames(exprMatrix) <- paste("Gene", 1:20, sep="")
colnames(exprMatrix) <- paste("Cell", 1:500, sep="")
##################################################
cells_rankings <- AUCell_buildRankings(exprMatrix, plotStats=TRUE, verbose=FALSE)
.check_AUCell_buildRankings_output(cells_rankings)
### Other input classes:
eset <- Biobase::ExpressionSet(assayData=exprMatrix)
rEset <- AUCell_buildRankings(eset, plotStats=FALSE)
testthat::expect_equal(class(rEset)[1], "aucellResults")
sexp <- SummarizedExperiment::SummarizedExperiment(assays=list(counts=exprMatrix))
rSexp <- AUCell_buildRankings(sexp, plotStats=FALSE)
testthat::expect_equal(class(rSexp)[1], "aucellResults")
sparseMat <- as(exprMatrix, "dgCMatrix")
rSparse <- AUCell_buildRankings(sparseMat, plotStats=FALSE, splitByBlocks=TRUE)
testthat::expect_equal(class(rSparse)[1], "aucellResults")
}
.check_AUCell_buildRankings_output <- function(cells_rankings)
{
testthat::expect_equal(ncol(cells_rankings), 500)
testthat::expect_equal(nrow(cells_rankings), 20)
testthat::expect_equal(getRanking(cells_rankings)['Gene13','Cell2'], 1)
testthat::expect_equal(class(cells_rankings)[1], "aucellResults")
testthat::expect_equal(SummarizedExperiment::assayNames(cells_rankings)[1], "ranking")
}
test_that("AUCell_buildRankings tests", test_AUCell_buildRankings())
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