Rp-Bp: Ribosome Profiling with Bayesian Predictions
Project description
Ribosome profiling with Bayesian predictions (Rp-Bp)
Ribosome profiling (Ribo-seq) is an RNA-sequencing-based readout of RNA translation. Isolation and deep-sequencing of ribosome-protected RNA fragments (ribosome footprints) provides a genome-wide snapshot of the translatome at sub-codon resolution. Rp-Bp is an unsupervised Bayesian approach to predict translated open reading frames (ORFs) from ribosome profiles. Rp-Bp can be used for ORF discovery, or simply to estimate periodicity in a set of Ribo-seq samples. When used for ORF discovery, Rp-Bp automatically classifies ORFs into different biotypes or categories, relative to their host transcript.
Rp-Bp comes with two interactive dashboards or web applications, one for read and periodicity quality control, the other to facilitate Ribo-seq ORFs discovery.
Documentation
Consult the user guide for instructions on how to install the package, or to use Docker/Singularity containers with the package pre-installed. Detailed usage instructions and tutorials are available.
How to report issues
For bugs, issues, or feature requests, use the bug tracker. Follow the instructions and guidelines given in the templates.
How to cite
Brandon Malone, Ilian Atanassov, Florian Aeschimann, Xinping Li, Helge Großhans, Christoph Dieterich. Bayesian prediction of RNA translation from ribosome profiling, Nucleic Acids Research, Volume 45, Issue 6, 7 April 2017, Pages 2960-2972.
License
The MIT License (MIT). Copyright (c) 2016 dieterich-lab.
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