The EVcouplings Python framework for coevolutionary sequence analysis
Thomas A. HopfiD, Anna G. GreeniD, Benjamin SchubertiD, Sophia Mersmann, Charlotta SchärfeiD, John IngrahamiD, Ágnes Tóth-PetróczyiD, Kelly P. BrockiD, Adam J. RiesselmaniD, Perry PalmedoiD, Chan Kang, Robert Sheridan, Eli J. DraizeniD, Christian DallagoiD, Chris SanderiD, Debora S. MarksiD
Abstract
SummaryCoevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. This approach requires extensive computational pipelines that integrate multiple tools, databases, and data processing steps. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The application has an easy to use command line interface to run workflows with user control over all analysis parameters, while the underlying modular Python package allows interactive data analysis and rapid development of new workflows. Through this multi-layered approach, the EVcouplings framework makes the full power of coevolutionary analyses available to entry-level and advanced users.\n\nAvailabilityhttps://github.com/debbiemarkslab/evcouplings\n\nContactsander.research@gmail.com, debbie@hms.harvard.edu
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 286
- FWCI
- 6.31
- Field percentile
- top 2%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- CoEVFold suite: user friendly pipelines to visually represent protein coevolution
Chris LB Graham, Liam Cremona, … Christopher D. A. Rodrigues·bioRxiv·Jan 26, 2026
- EVfold.org: Evolutionary Couplings and Protein 3D Structure Prediction
Robert Sheridan, Robert J. Fieldhouse, … Chris Sander·bioRxiv·Jul 2, 2015
- Evolutionary couplings detect side-chain interactions
A. J. Hockenberry, C. O. Wilke·bioRxiv·Dec 20, 2018
- pydca v1.0: a comprehensive software for Direct Coupling Analysis of RNA and Protein Sequences
Mehari B. Zerihun, Fabrizio Pucci, … Alexander H. Schug·BioinformaticsPeer-reviewed·Nov 26, 2019
- From Sequence to Function: Coevolving Amino Acids Encode Structural and Functional Domains
Daniele Granata, Luca Ponzoni, … Vincenzo Carnevale·Proceedings of the National Academy of SciencesPeer-reviewed·Nov 28, 2017
- COCOA-Tree: Phylogenetic visualization and comparative analysis of coevolving residues
Margaux Jullien, Marion Chauveau, … Ivan Junier·bioRxiv·Sep 25, 2026