tests/testthat/test_zero_zero.R

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

context("zero_zero")	
test_that("contrast of two groups with all zeros - LFC zeroed out", {	

  # test comparison of two groups with all zeros
  dds <- makeExampleDESeqDataSet(m=8, n=100, sizeFactors=c(1,1,.5,.5,1,1,2,2))
  dds$condition <- factor(rep(c("A","B","C","D"),each=2))
  counts(dds)[1,] <- c(100L,110L,0L,0L,100L,110L,0L,0L)
  counts(dds)[2,] <- rep(0L, 8)
  #plot(counts(dds)[1,] ~ dds$condition)
  dds <- DESeq(dds)

  res <- results(dds, contrast=c("condition","D","B"))[1,]
  expect_equal(res$log2FoldChange, 0)
  res <- results(dds, contrast=c(0,-1,0,1))[1,]
  expect_equal(res$log2FoldChange, 0)
  # list works too, because it's converted to numeric
  res <- results(dds, contrast=list("condition_D_vs_A","condition_B_vs_A"))[1,]
  expect_equal(res$log2FoldChange, 0)
  
  res <- results(dds, name="condition_D_vs_A")[1,]
  expect_true(res$log2FoldChange != 0)
  res <- results(dds,c(0,0,0,1))[1,]
  expect_true(res$log2FoldChange != 0)

  # if all samples have 0, should be NA
  res <- results(dds, contrast=c("condition","D","B"))[2,]
  expect_true(is.na(res$log2FoldChange))
  res <- results(dds, contrast=c(0,-1,0,1))[2,]
  expect_true(is.na(res$log2FoldChange))

})