# Analysis of gene differential expression.

`deGene.Rd`

Analyzes gene-level differential expression using DESeq2 method (Love et al., 2014).

    deGene(object,comparePairs=list(c("control","treat")), pval = 0.01,
     useMultiCore=FALSE, numCores = NULL)

    # S4 method for TSSr
    deGene(
      object,
      comparePairs = list(c("control", "treat")),
      pval = 0.01,
      useMultiCore = FALSE,
      numCores = NULL
    )

## Arguments

object | A TSSr object.
comparePairs | Specified list of sample pairs for comparison with DESeq2 method.
pval | Genes with adjusted p value >= pVal will be returned. Default value = 0.01.
useMultiCore | Logical indicating whether multiple cores are used (TRUE) or not (FALSE). Default is FALSE.
numCores | Number of cores are used in clustering step. Used only if useMultiCore = TRUE. Default is NULL.

## Examples

    # \donttest{
    deGene(exampleTSSr,comparePairs=list(c("control","treat")), pval = 0.01)#>
    #> Calculating gene differential expression...#> converting counts to integer mode#> estimating size factors#> estimating dispersions#> gene-wise dispersion estimates#> mean-dispersion relationship#> final dispersion estimates#> fitting model and testing# }