# sample dataset
samples_num <- 11
genes_num <- 100
dataTestSV <- matrix(rnbinom(genes_num*samples_num,mu=150,size=2),ncol=samples_num)
rownames(dataTestSV)<- paste0("gene",1:genes_num)
colnames(dataTestSV) = c("V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11")
dataTestSV[is.infinite(dataTestSV)] <- 5
covTestSV <- data.frame(a=c(rep("aa",3),rep("bb",4),rep("cc",4)),
b=c(1,2,3,4,5,6,7,8,9,0,0),
class=c(rep("A",5),rep("B",6)),
row.names = c(
"V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11"))
# check object type
expect_true("class" %in% colnames(covTestSV))
expect_true(identical(colnames(dataTestSV), rownames(covTestSV)))
#expected error
expect_error(DaMiR.makeSE())
expect_error(DaMiR.makeSE(dataTestSV="data.frame"))
expect_error(DaMiR.makeSE(covTestSV="matrix"))
# launch function
SEtest <- DaMiR.makeSE(dataTestSV,covTestSV)
# check results
expect_true(all(rownames(SEtest) == rownames(dataTestSV)))
expect_true(all(colnames(SEtest) == colnames(dataTestSV)))
expect_is(SEtest, "SummarizedExperiment")
expect_true("class" %in% colnames(SEtest@colData))
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