DESeq2.createRmd {compcodeR} | R Documentation

## Generate a `.Rmd` file containing code to perform differential expression analysis with DESeq2

### Description

A function to generate code that can be run to perform differential expression analysis of RNAseq data (comparing two conditions) using the DESeq2 package. The code is written to a `.Rmd` file. This function is generally not called by the user, the main interface for performing differential expression analysis is the `runDiffExp` function.

### Usage

    DESeq2.createRmd(data.path, result.path, codefile, fit.type, test,
      beta.prior = TRUE, independent.filtering = TRUE,
      cooks.cutoff = TRUE, impute.outliers = TRUE)

### Arguments

`data.path` | The path to a .rds file containing the `compData` object that will be used for the differential expression analysis.
`result.path` | The path to the file where the result object will be saved.
`codefile` | The path to the file where the code will be written.
`fit.type` | The fitting method used to get the dispersion-mean relationship. Possible values are `"parametric"`, `"local"` and `"mean"`.
`test` | The test to use. Possible values are `"Wald"` and `"LRT"`.
`beta.prior` | Whether or not to put a zero-mean normal prior on the non-intercept coefficients. Default is `TRUE`.
`independent.filtering` | Whether or not to perform independent filtering of the data. With independent filtering=TRUE, the adjusted p-values for genes not passing the filter threshold are set to NA.
`cooks.cutoff` | The cutoff value for the Cook's distance to consider a value to be an outlier. Set to Inf or FALSE to disable outlier detection. For genes with detected outliers, the p-value and adjusted p-value will be set to NA.
`impute.outliers` | Whether or not the outliers should be replaced by a trimmed mean and the analysis rerun.

### Details

For more information about the methods and the interpretation of the parameters, see the `DESeq2` package and the corresponding publications.

### Value

The function generates a `.Rmd` file containing the code for performing the differential expression analysis. This file can be executed using e.g. the `knitr` package.

### Author(s)

Charlotte Soneson

### References

Anders S and Huber W (2010): Differential expression analysis for sequence count data. Genome Biology 11:R106

### Examples

    try(
    if (require(DESeq2)) {
    tmpdir <- normalizePath(tempdir(), winslash = "/")
    mydata.obj <- generateSyntheticData(dataset = "mydata", n.vars = 1000,
                                        samples.per.cond = 5, n.diffexp = 100,
                                        output.file = file.path(tmpdir, "mydata.rds"))
    runDiffExp(data.file = file.path(tmpdir, "mydata.rds"), result.extent = "DESeq2",
               Rmdfunction = "DESeq2.createRmd",
               output.directory = tmpdir, fit.type = "parametric",
               test = "Wald")
    })

[Package compcodeR version 1.20.1 Index]