Getting started#

What is Rp-Bp?#

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.

To get started, you need

Ribo-seq data (FASTQ)
genome sequence and annotation for your organism (FASTA, GTF)
ribosomal sequence for in-silico rRNA removal (FASTA)
protocol-specific or general adapter sequences to be removed (FASTA)

Installation#

Install with

# set up the conda channels if required
# conda config --add channels defaults
# conda config --add channels bioconda
# conda config --add channels conda-forge
# conda config --set channel_priority strict

# create a conda environment called rpbp and install rpbp
conda create -n rpbp rpbp

or use a container

# docker or...
docker pull quay.io/biocontainers/rpbp:<tag>
# ...singularity
singularity pull rpbp.sif docker://quay.io/biocontainers/rpbp:<tag>

There is no latest tag, you need to specify the version tag. See rpbp/tags for valid values for <tag>.

For detailed installation instructions, refer to Installation.

Rp-Bp quickstart#

In a nutshell, you need to prepare genome indices and annotations for your organism by calling

prepare-rpbp-genome <config> [options]

To estimate periodicity on a set of Ribo-seq samples, or to run the ORF discovery pipeline, simply call

run-all-rpbp-instances <config> [options]

To get started, the package also includes a small example using a C. elegans dataset. Check the Tutorials.

For more information and guidelines on how to prepare the configuration file, refer to the User guide. For visualisation and quality control, see Visualization and quality control.

How to report issues#

Bugs and issues should be reported in the bug tracker. Follow the instructions and guidelines given in the template.

How to contribute#

Contributions are welcome! New code should follow Black and flake8. Install development dependencies inside a virtual environment, see Contributing to Rp-Bp. A typical development workflow would include (i) forking the repository, (ii) creating a new branch for your PR, (iii) adding features or bug fixes, (iv) making sure all tests are passing, (v) building the documentation if necessary, and (vi) opening a PR back to the main repository. If you’re fixing a bug, add a test. Run it first to confirm it fails, then fix the bug, and run it again to confirm it’s fixed. If adding a new feature, add a test, or first open an issue to discuss the idea.

Running the tests#

We use pytest to test Rp-Bp. Currently, only regression tests are implemented. Dependencies can be installed with pip install -e .[tests].

Building the docs#

Dependencies for building the documentation can be installed with pip install -e .[docs].

Semantic versioning#

We try to follow semantic versioning.

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.