compcodeR (version 1.8.2)

edgeR.GLM.createRmd: Generate a .Rmd file containing code to perform differential expression analysis with the edgeR GLM approach

Description

A function to generate code that can be run to perform differential expression analysis of RNAseq data (comparing two conditions) using the GLM functionality from the edgeR 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

edgeR.GLM.createRmd(data.path, result.path, codefile, norm.method, disp.type, disp.method, trended)

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.

norm.method

The between-sample normalization method used to compensate for varying library sizes and composition in the differential expression analysis. Possible values are "TMM", "RLE", "upperquartile" and "none".

disp.type

The type of dispersion estimate used. Possible values are "common", "trended" and "tagwise".

disp.method

The method used to estimate the dispersion. Possible values are "CoxReid", "Pearson" and "deviance".

trended

Logical parameter indicating whether or not a trended dispersion estimate should be used.

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.

Details

For more information about the methods and the interpretation of the parameters, see the edgeR package and the corresponding publications.

References

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

Examples

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 = "edgeR.GLM",
           Rmdfunction = "edgeR.GLM.createRmd",
           output.directory = tmpdir, norm.method = "TMM",
           disp.type = "tagwise", disp.method = "CoxReid",
           trended = TRUE)