Archived Code Collection:

Associated with the paper:
A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function

This repository is no longer maintained!

Please use the actively maintained implementation of JPLE here:
https://github.com/morrislab/jple

If you want to use JPLE to train your own model for predicting sequence specificity profiles from protein sequence, or to infer RNA sequence specificity for RRM- or KH-domain RNA-binding proteins, please refer to: https://github.com/morrislab/jple

All the measured and inferred RNA sequence specificities can be found at:
cisbp.org

Repository Contents

This repository serves as an archival collection of scripts and command-line tools used for analyses during the PhD thesis:
Inferring RNA Sequence Specificities from Protein Sequences to Characterize Post-Transcriptional Regulation in Eukaryotes

Maintenance is limited, but the repository contains the scripts used to reproduce figures and results presented in the thesis.

Recommended setup

The majority of scripts will run on a virtual environment with python 2.7 adding dependencies listed in dependencies.txt

Some scripts may require python3 or other dependencies. Please install as required:

• python3 (agglomerative_clustering.py), scikit-learn==0.23.2)
• Hmmer (http://hmmer.org/)
• conservation_code (Capra JA and Singh M. Predicting functionally important residues from sequence conservation. Bioinformatics, 23(15):1875-82, 2007. (https://compbio.cs.princeton.edu/conservation/))
• pymol (https://pymol.org/2/) to visualize individual pdbs

Reproduce thesis results:

To reconstruct the figures (fig1-5.sh), first run the preprocessing scripts in the following order:

1. rncmpt_data.sh
2. fig1.sh
3. performance_calc.sh
4. interface_importance.sh
5. fig2.sh
6. jple_reconstruction.sh
7. fig3.sh
8. cisbp-recstats.sh
9. arabidopsis.sh
10. fig4.sh
11. fig5.sh

License

The repository is licensed under the BSD 3-Clause License. See LICENSE for details.

Citation

If you use this code, please cite the following:

• Primary paper:

  Sasse A., Ray D., Laverty, K.U. et al. A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function. Nature Biotechnology (2025). https://doi.org/10.1038/s41587-025-02733-6

• PhD Thesis:

  Sasse A. Inferring RNA Sequence Specificities from Protein Sequences to Characterize Post-Transcriptional Regulation in Eukaryotes. PhD Thesis, University of Toronto (2021). Proquest link