Nothing
context("Test validity")
test_that("Test invalid input", {
n = 10
m = 30
counts = matrix(rnbinom(n * m, 10, 0.3), n)
var1 = rnorm(m)
var2 = rnorm(m)
var3 = rnorm(m)
var4 = as.factor(sample(c(0,1,2), m, replace = TRUE))
colData = data.frame(var1 = var1, var2 = var2,
var3 = var3, var4 = var4)
counts1 = counts
counts1[1,1] = "1"
expect_error(NBAMSeqDataSet(counts1, colData, design = ~ s(var1)))
counts2 = counts
counts2[1,1] = NA
expect_error(NBAMSeqDataSet(counts2, colData, design = ~ s(var1)))
counts3 = counts
counts3[1,1] = 3.5
expect_message(NBAMSeqDataSet(counts3, colData, design = ~ s(var1)),
"countData contains non-integers, rounded to the nearest
integer automatically.")
counts4 = counts
counts4[1,1] = -5
expect_error(NBAMSeqDataSet(counts4, colData, design = ~ s(var1)))
design1 = matrix(sample(m*4), m, 4)
expect_error(NBAMSeqDataSet(counts, colData, design = design1))
expect_error(NBAMSeqDataSet(countData = counts, colData = colData,
design = ~ var4 + s(var1) + var2 + var3 + var5))
colData2 = colData
colData2$var1 = sample(c("normal", "tumor"), m, replace = TRUE)
expect_error(NBAMSeqDataSet(countData = counts, colData = colData2,
design = ~ var4 + var1 + s(var2) + var3))
expect_error(NBAMSeqDataSet(countData = counts, colData = colData,
design = ~ var4 + var1 + var2 + var3))
expect_error(NBAMSeqDataSet(countData = counts, colData = colData,
design = ~ s(var4) + var1 + var2 + var3),
"Non linear term can not be a factor.")
counts5 = counts
counts5[1:2,] = 0
expect_message(NBAMSeqDataSet(counts5, colData, design = ~ s(var1)),
"2 genes have all 0 counts for all samples. Consider filtering out these genes
before differential expression analysis.")
counts6 = matrix(0,n,m)
expect_error(NBAMSeqDataSet(counts6, colData, design = ~ s(var1)))
})
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