BayesPairing2: Identifying RNA 3D modules in sequence and alignments

This is a fork of BayesPairing 2 to be used within the context of a larger Bioionformatics pipeline. For info on BayesPairing, please click here.

Major Changes

Changes to the official branch of BayesPairing (continually updated)

• BayesPairing previously operated by use of absolute imports/references to file paths. These were switched to relative imports in-order to allow it to fit within the project architecture.

What's New

• A flask layer that allows BayesPairing to be called from an endpoint. This includes endpoints for file input & string input as well as another to retrieve representative graphs from a module database.
• BayesPairing has also been dockerized, and a dockerfile is provided.
• Three additional classes are created within core/src/pipeline.
  • pipeline_bp: A modification of run_fasta from parse_sequences that does not save output to files
  • pipeline_chefschoice: A modification of key methods from chefs_choice that handle SVG generation
  • chefs_assistant: a new class that handles virtually all heavy lifting and processing of the BP service
• Testing! Located within the tests directory! Because BP results are non-deterministic, these mainly validate that results are successful or a failure and whether keys exist, not the exact contents of a specific result.
• TravisCI will automatically run tests after each commit

The command line program remains functional, but must now be run from the root directory instead of src. Here is a sample run:

python3 -m core.src.parse_sequences -seq "UUUUUUAAGGAAGAUCUGGCCUUCCCACAAGGGAAGGCCAAAGAAUUUCCUU" -samplesize 1000 -t 4 -d ALL

Note that you must first set-up and activate the Anaconda environment (requirements provided in environment.yml).

This package includes tools for:

• Identifying RNA 3D modules in a sequence
• Creating your own BayesPairing models
• RNA 3D module plotting
• Searching for modules in many sequences separately (fasta format)
• Searching for modules in alignments (stockholm format)
• Identifying modules in sequences with known secondary structure.

BayesPairing2 was accepted to RECOMB 2020

The article is available on biorxiv: https://www.biorxiv.org/content/10.1101/834762v1.abstract

Requirements (installed via conda)

• Python 3.6+
• Docker
• Flask
• Gunicorn
• Networkx 2.1+
• BioPython
• matplotlib
• weblogo
• wrapt
• anytree
• pgmpy (included)
• RNAlib (viennaRNA)
• LaTeX (optional)

Contact

For inquiries on BayesPairing specifically, please contact:

Roman Sarrazin-Gendron [email protected]

For inquiries regarding the overall pipeline as well as top level code including the Flask/Docker layer, please open an issue.