DESeq2.createRmd: Generate a '.Rmd' file containing code to perform...

In csoneson/compcodeR: RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods

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,
  nas.as.ones = FALSE
)

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.
nas.as.ones	Whether or not adjusted p values that are returned as NA by DESeq2 should be set to 1. This option is useful for comparisons with other methods. For more details, see section "I want to benchmark DESeq2 comparing to other DE tools" from the DESeq2 vignette (available by running vignette("DESeq2", package = "DESeq2")). Default to FALSE.

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")
})

csoneson/compcodeR documentation built on Oct. 25, 2023, 1:28 a.m.