View source: R/generateRmdCodeDiffExp.R
ttest.createRmd | R Documentation |
.Rmd
file containing code to perform differential expression analysis with a t-testA function to generate code that can be run to perform differential expression analysis of RNAseq data (comparing two conditions) using a t-test, applied to the normalized counts. 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.
ttest.createRmd(data.path, result.path, codefile, norm.method)
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. |
norm.method |
The between-sample normalization method used to compensate for varying library sizes and composition in the differential expression analysis. The normalization factors are calculated using the |
For more information about the methods and the interpretation of the parameters, see the edgeR
package 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
Robinson MD, McCarthy DJ and Smyth GK (2010): edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140
Robinson MD and Oshlack A (2010): A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology 11:R25
try(
if (require(genefilter)) {
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 = "ttest",
Rmdfunction = "ttest.createRmd",
output.directory = tmpdir, norm.method = "TMM")
})
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