runDESeq2 {debrowser} | R Documentation

## runDESeq2

### Description

Run DESeq2 algorithm on the selected conditions. Output is to be used for the interactive display.

### Usage

    runDESeq2(data = NULL, columns = NULL, conds = NULL,
      fitType = c("parametric", "local", "mean"), betaPrior = 0,
      testType = c("Wald", "LRT"), rowsum.filter = 10)

### Arguments

`data,` | A matrix that includes all the expression raw counts, rownames has to be the gene, isoform or region names/IDs
`columns,` | is a vector that includes the columns that are going to be analyzed. These columns has to match with the given data.
`conds,` | experimental conditions. The order has to match with the column order
`fitType,` | either "parametric", "local", or "mean" for the type of fitting of dispersions to the mean intensity. See estimateDispersions for description.
`betaPrior,` | whether or not to put a zero-mean normal prior on the non-intercept coefficients See nbinomWaldTest for description of the calculation of the beta prior. By default, the beta prior is used only for the Wald test, but can also be specified for the likelihood ratio test.
`testType,` | either "Wald" or "LRT", which will then use either Wald significance tests (defined by nbinomWaldTest), or the likelihood ratio test on the difference in deviance between a full and reduced model formula (defined by nbinomLRT)
`rowsum.filter,` | regions/genes/isoforms with total count (across all samples) below this value will be filtered out

### Value

deseq2 results

### Examples

        x <- runDESeq2()

[Package debrowser version 1.6.8 Index]