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
# 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 [options] config

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

run-all-rpbp-instances [options] config

For more information and guidelines how to prepare the configuration file and run the pipeline, refer to the User guide. For visualization and quality control, see Visualization and QC.

To get started, the package includes a small example dataset. Check the Tutorials.

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.

License

The MIT License (MIT). Copyright (c) 2016 dieterich-lab.