An R package for the analysis, meta-analysis and result reporting of RNA-Seq gene expression data - Next Generation!
if (!requireNamespace("BiocManager",quietly=TRUE))
install.packages("BiocManager")
library(BiocManager)
BiocManager::install("metaseqR2")
# or for development version to be installed
# BiocManager::install("metaseqR2",version="devel")
Use with caution as the latest version may be unstable, although typical Bioconductor checks are executed before each push.
if (!requireNamespace("devtools",quietly=TRUE))
install.packages("devtools")
library(devtools)
install_github("pmoulos/metaseqR2")
The same things apply regarding stability.
git clone https://github.com/pmoulos/metaseqR2.git
mkdir metaseqR2-build
rsync -avr --exclude=README.md --exclude=.git --exclude=.gitignore \
./metaseqR2-local/ ./metaseqR2-build/metaseqR2
cd ./metaseqR2-build
R CMD build ./metaseqR2
This will take some time to build the vignettes. If you do not need them:
R CMD build --no-build-vignettes ./metaseqR2
And then install
R CMD INSTALL ./metaseqR2_x.y.z.tar.gz
Please report any issues here.
If you do not wish to build annotation databases on your own using the
buildAnnotationDatabase
function, you can find complete pre-built
annotation SQLite databases
here.
New versions will be constructed from time to time, most probably whenever a new
Ensembl release comes live.
The prebuilt annotations contain:
The SQLite database must be placed in system.file(package="metaseqR2")
and
named annotation.sqlite
, that is
file.path(system.file(package="metaseqR2"),"annotation.sqlite")
. Otherwise
you will have to provide your desired location in each metaseqr2
call.
Alternatively, on-the-fly download is still supported but is inneficient.
metaseqR2 would benefit from the existence of all the following packages:
A recent version of Pandoc is also required, ideally above 2.0.
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