epytope - An Immunoinformatics Framework for Python

Copyright 2014 by Benjamin Schuber, Mathias Walzer, Philipp Brachvogel, Andras Szolek, Christopher Mohr, and Oliver Kohlbacher

epytope is a framework for T-cell epitope detection, and vaccine design. It offers consistent, easy, and simultaneous access to well established prediction methods of computational immunology. epytope can handle polymorphic proteins and offers analysis tools to select, assemble, and design linker sequences for string-of-beads epitope-based vaccines. It is implemented in Python in a modular way and can easily be extended by user defined methods.

Copyright

epytope is released under the three clause BSD license.

Installation

use the following commands:

pip install git+https://github.com/KohlbacherLab/epytope

Dependencies

Python Packages

• pandas
• pyomo>=4.0
• svmlight
• PyMySQL
• biopython
• pyVCF
• h5py<=2.10.0

Third-Party Software (not installed through pip)

• NetMHC predictor family (NetMHC(pan)-(I/II), NetChop, NetCTL) (http://www.cbs.dtu.dk/services/software.php)
• PickPocket (http://www.cbs.dtu.dk/services/software.php)
• Integer Linear Programming Solver (recommended CBC: https://projects.coin-or.org/Cbc)

Please pay attention to the different licensing of third party tools.

Framework summary

Currently epytope provides implementations of several prediction methods or interfaces to external prediction tools.

• Cleavage Prediction
  • Proteasomal cleavage matrix-based prediction by Dönnes et al.
  • ProteaSMM by Tenzer et al.
  • NetChop 3.1
• Epitope Assembly
  • Approach by Toussaint et al.
  • Bi-objective extension of approach by Toussaint et al.
  • Assembly with spacers by Schubert et al.
• Epitope Prediction
  • SYFPEITHI
  • MHCNuggets 2.0, 2.3.2
  • MHCflurry 1.2.2, 1.4.3
  • NetMHC 3.0, 3.4, 4.0
  • NetMHCII 2.2, 2.3
  • NetMHCpan 2.4, 2.8, 3.0, 4.0, 4.1
  • NetMHCIIpan 3.0, 3.1, 4.0, 4.1
  • PickPocket 1.1
  • NetCTLpan 1.1
• Epitope Selection
  • OptiTope
• Stability Prediction
  • NetMHCstabpan 1.0
• TAPP Prediction
  • TAP prediction model by Doytchinova et al.
  • SMMTAP

Getting Started

Users and developers should start by reading our wiki and IPython tutorials. A reference documentation is also available online.

How to Cite

Please cite

Schubert, B., Walzer, M., Brachvogel, H-P., Sozolek, A., Mohr, C., and Kohlbacher, O. (2016). FRED 2 - An Immunoinformatics Framework for Python. Bioinformatics 2016; doi: 10.1093/bioinformatics/btw113

and the original publications of the used methods.