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

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

Description

A function to generate code that can be run to perform differential expression analysis of RNAseq (comparing two conditions) by applying the variance-stabilizing transformation of the DESeq package followed by differential expression analysis using limma. 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

vst.limma.createRmd(data.path, result.path, codefile, fit.type)

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" and "local".

Details

For more information about the methods and the interpretation of the parameters, see the limma and DESeq packages 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

Smyth GK (2005): Limma: linear models for microarray data. In: 'Bioinformatics and Computational Biology Solutions using R and Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds), Springer, New York, pages 397-420

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

Examples

try(
if (require(DESeq)) {
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 = "vst.limma",
           Rmdfunction = "vst.limma.createRmd",
           output.directory = tmpdir, fit.type = "parametric")
})

Bioconductor-mirror/compcodeR documentation built on June 1, 2017, 6:39 a.m.