As it currently stands, this package lives on the devel branch, and it is not on the current release (Bioconductor 3.10). Please use the alternative installation instructions given above.
RiboR will be available via Bioconductor on the next release cycle (Bioconductor 3.11) which is scheduled for the end of April.
Once it is available, the download instructions will be as follows.
Install Latest Version from Bioconductor (Not Yet Available)
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
@article{ozadam2020riboflow,
title={RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution},
author={Ozadam, Hakan and Geng, Michael and Cenik, Can},
journal={Bioinformatics},
volume={36},
number={9},
pages={2929--2931},
year={2020},
publisher={Oxford University Press}
}
RiboR
R interface for .ribo files
Ribo Ecosystem
The paper associated with this package and its larger ecosystem can be found here.
Installation
RiboR requires R version 3.6 or higher.
Note For Linux Users
Install dependencies for devtools. For Ubuntu based distributions, you can use the following command.
sudo apt-get install libxml2-dev libcurl4-openssl-dev libssl-dev build-essential m4 autoconf -yInstall Latest Version From GitHub
install.packages("devtools")library("devtools")install_github("ribosomeprofiling/ribor")Note for Bioconductor Installation
As it currently stands, this package lives on the
develbranch, and it is not on the current release (Bioconductor 3.10). Please use the alternative installation instructions given above.RiboR will be available via Bioconductor on the next release cycle (Bioconductor 3.11) which is scheduled for the end of April.
Once it is available, the download instructions will be as follows.
Install Latest Version from Bioconductor (Not Yet Available)
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")BiocManager::install("ribor")Documentation
Here is a walk-through of RiboR.
Citing
RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution, H. Ozadam, M. Geng, C. Cenik Bioinformatics 36 (9), 2929-2931