Description Usage Arguments Details Value Author(s) References Examples
View source: R/edgeR.GLMQL.createRmd.R
A function to generate code that can be run to perform differential expression analysis of RNAseq data (comparing two conditions) using the edgeR package.
1 2 | edgeR.GLMQL.createRmd(data.path, result.path, codefile,
norm.method = "TMM", disp.estimation = "CoxReid")
|
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 |
A Character parameter for calcNormFactors function. Possible values are "TMM", "TMMwzp", "RLE", "upperquartile", or "none". |
disp.estimation |
A Character parameter for estimateGLMCommonDisp function. Possible values are "CoxReid", "Pearson" or "deviance". |
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.
BuKyung Baik
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
Lun, ATL, Chen, Y, and Smyth, GK (2016). It’s DE-licious: a recipe for differential expression analyses of RNA-seq experiments using quasi-likelihood methods in edgeR. Methods in Molecular Biology 1418, 391–416.
1 2 3 4 5 6 7 | tmpdir <- normalizePath(tempdir(), winslash = "/")
SyntheticDataSimulation(simul.data= 'KIRC', dataset = file.path(tmpdir, "mydata.rds"), n.var = 500,
samples.per.cond = 3, n.diffexp = 100, dispType='same', mode='D',
fraction.upregulated=0.5, dataset.parameters=generateDatasetParameter())
compcodeR::runDiffExp(data.file = file.path(tmpdir, "mydata.rds"), result.extent = "edgeR.GLMQL",
Rmdfunction = "edgeR.GLMQL.createRmd",
output.directory = tmpdir)
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