tests/testthat/test_edge_case.R

In DESeq2: Differential gene expression analysis based on the negative binomial distribution

context("edge_case")
test_that("edge cases work or throw proper errors", {
  # one row
  set.seed(1)
  dds <- makeExampleDESeqDataSet(n=1)
  sizeFactors(dds) <- rep(1,ncol(dds))
  dispersions(dds) <- .5
  dds <- nbinomWaldTest(dds)
  res <- results(dds)
  dds <- nbinomLRT(dds, reduced=~1)
  res <- results(dds)


  # only intercept
  set.seed(1)
  dds <- makeExampleDESeqDataSet(n=100)
  design(dds) <- ~ 1
  expect_warning({dds <- DESeq(dds)})
  res <- results(dds)


  # metadata insertion
  dds <- makeExampleDESeqDataSet(n=50,m=4)

  dds2 <- DESeqDataSetFromMatrix( counts(dds), colData(dds), design(dds) )
  mcols(dds2)$foo <- paste( "bar", 1:nrow(dds2) )
  dds2 <- DESeq(dds2)
  results(dds2)
  expect_true(class(mcols(mcols(dds2))$type) == "character")

  dds3 <- DESeqDataSetFromMatrix( counts(dds), DataFrame(row.names=colnames(dds)), ~ 1 )
  dds3$test <- 1:ncol(dds3)
  dds3 <- estimateSizeFactors(dds3)
  expect_true(class(mcols(colData(dds3))$type) == "character")


  # underscores
  dds <- makeExampleDESeqDataSet(n=50,m=4)
  levels(dds$condition) <- c("A_1","B_2")
  dds$exp_cond <- dds$condition
  design(dds) <- ~ exp_cond
  dds <- DESeq(dds)
  results(dds)

  # NA in colData
  dds <- makeExampleDESeqDataSet(n=50,m=4)
  colData(dds)$condition[4] <- NA
  expect_error(DESeq(dds))
})