inst/unitTests/test_fringeCases.R

In aghozlane/DESeq2shaman: Differential gene expression analysis based on the negative binomial distribution

test_oneRow <- function() {
  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)
}

test_onlyIntercept <- function() {
  set.seed(1)
  dds <- makeExampleDESeqDataSet(n=100)
  design(dds) <- ~ 1
  dds <- DESeq(dds)
  res <- results(dds)
}

test_metadataInsertion <- function() {
  dds <- makeExampleDESeqDataSet(n=50,m=4)
  
  dds2 <- DESeqDataSetFromMatrix( counts(dds), colData(dds), design(dds) )
  mcols(dds2)$foo <- paste( "bar", 1:nrow(dds2) )
  dds2 <- DESeq(dds2)
  results(dds2)
  checkTrue(class(mcols(mcols(dds2))$type) == "character")

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

test_underscores <- function() {
  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)
}