The EVcouplings Python framework for coevolutionary sequence analysis

Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The fra...

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Published inBioinformatics (Oxford, England) Vol. 35; no. 9; pp. 1582 - 1584
Main Authors Hopf, Thomas A, Green, Anna G, Schubert, Benjamin, Mersmann, Sophia, Schärfe, Charlotta P I, Ingraham, John B, Toth-Petroczy, Agnes, Brock, Kelly, Riesselman, Adam J, Palmedo, Perry, Kang, Chan, Sheridan, Robert, Draizen, Eli J, Dallago, Christian, Sander, Chris, Marks, Debora S
Format Journal Article
LanguageEnglish
Published England Oxford University Press 01.05.2019
Subjects
Applications Notes
Proteins
RNA
Sequence Alignment
Sequence Analysis
Software
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Summary:Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. 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 combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. https://github.com/debbiemarkslab/evcouplings.
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USDOE
FG02-97ER25308; U41 HG006623; NRNB P41 GM103504; R01 GM106303
The authors wish it to be known that, in their opinion, Thomas A. Hopf, Anna G. Green and Benjamin Schubert authors should be regarded as Joint First Authors.
The authors wish it to be known that, in their opinion, Chris Sander and Debora S. Marks authors should be regarded as Joint Senior Authors.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/bty862