vst.limma.createRmd {compcodeR} | R Documentation |
.Rmd
file containing code to perform differential expression analysis with limma after the variance-stabilizing transformation provided in DESeqA 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.
vst.limma.createRmd(data.path, result.path, codefile, fit.type)
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 |
For more information about the methods and the interpretation of the parameters, see the limma
and DESeq
packages and the corresponding publications.
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.
Charlotte Soneson
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
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") })