rnaglib 2.0.12

RNAglib: Tools for learning on the structure of RNA using 2.5D geometric representations

RNA Geometric Library (rnaglib)

RNAglib is a Python package for studying RNA 2.5D and 3D structures. Functionality includes automated data loading, analysis, visualization, ML model building and benchmarking.

We host RNAs annotated with molecule, base pair, and nucleotide level attributes. These include, but are not limited to:

• Secondary structure
• 3D coordinates
• Protein binding
• Small molecule binding
• Chemical modifications
• Leontis-westhof base pair geometry classification

Cite

@article{mallet2022rnaglib,
  title={RNAglib: a python package for RNA 2.5 D graphs},
  author={Mallet, Vincent and Oliver, Carlos and Broadbent, Jonathan and Hamilton, William L and Waldisp{\"u}hl, J{\'e}r{\^o}me},
  journal={Bioinformatics},
  volume={38},
  number={5},
  pages={1458--1459},
  year={2022},
  publisher={Oxford University Press}
}

Data

Data can be downloaded directrly from Zenodo or through the provided command line utility $ rnaglib_download.

Version	Date	Total RNAs	Total Non-Redundant	Non-redundant version	rnaglib commit
1.0.0	15-02-23	5759	1176	3.269	5446ae2c
0.0.0	20-07-21	3739	899	3.186	eb25dabd

Installation

The package can be cloned and the source code used directly. We also deploy it as a pip package and recommend using this install in conda environments.

If one wants to use GPU support, one should install Pytorch and DGL with the appropriate options. Otherwise you can just skip this step and the pip installs of Pytorch and DGL will be used.

Then, one just needs to run :

pip install rnaglib

Then one can start using the packages functionalities by importing them in one's python script.

Optional Dependencies

To build 2.5D graphs from scratch locally, for the moment you need to install a fork of fr3d-python manually.

pip install git+https://github.com/cgoliver/fr3d-python.git

Associated Repositories:

VeRNAl

RNAMigos

Resources

• Documentation
• Homepage
• Twitter
• Contact: [e-mail]

References

1. Leontis, N. B., & Zirbel, C. L. (2012). Nonredundant 3D Structure Datasets for RNA Knowledge Extraction and Benchmarking. In RNA 3D Structure Analysis and Prediction N. Leontis & E. Westhof (Eds.), (Vol. 27, pp. 281–298). Springer Berlin Heidelberg. doi:10.1007/978-3-642-25740-7_13