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Rp-Bp: Ribosome profiling with Bayesian predictions
===================================================

Introduction
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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. Aligned by their P-site positions, the footprints from actively translating ribosomes exhibit a 3-nt periodicity. **Rp-Bp** takes advantage of this periodic signal to select reads and predict translation.

**Rp-Bp** is an unsupervised Bayesian approach to predict translated open reading frames (ORFs) from ribosome profiles, using the automatic Bayesian Periodic fragment length and ribosome P-site offset Selection (BPPS), *i.e.* read lengths and ribosome P-site offsets are inferred from the data, without supervision. **Rp-Bp** is able to handle *de novo* translatome annotation by directly assessing the periodicity of the Ribo-seq signal.

**Rp-Bp** can be used for ORF discovery, or simply to estimate periodicity in a set of Ribo-seq replicates, *e.g.* to know which samples and read lengths are usable for downstream analyses. When used for ORF discovery, **Rp-Bp** automatically classifies ORFs into different biotypes or categories, relative to their host transcript.


.. toctree::
   :titlesonly:

   getting-started
   installation
   user-guide
   tutorial
   faq
   api