# 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

1 2 3 | ```
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 |

`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 |

`test` |
The test to use. Possible values are |

`beta.prior` |
Whether or not to put a zero-mean normal prior on the non-intercept coefficients. Default is |

`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

1 2 3 4 5 6 7 8 9 10 11 | ```
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")
})
``` |