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epytope-3.3.1
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مشاهده بیشترتوضیحات
A Framework for Epitope Detection and Vaccine Design
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | epytope-3.3.1 |
| نام | epytope |
| نسخه کتابخانه | 3.3.1 |
| نگهدارنده | ['Christopher Mohr'] |
| ایمیل نگهدارنده | ['christopher.mohr@uni-tuebingen.de'] |
| نویسنده | Benjamin Schubert, Mathias Walzer, Christopher Mohr, Leon Kuchenbecker |
| ایمیل نویسنده | benjamin.schubert@helmholtz-muenchen.de, walzer@ebi.ac.uk, christopher.mohr@uni-tuebingen.de, leon.kuchenbecker@uni-tuebingen.de |
| آدرس صفحه اصلی | https://github.com/KohlbacherLab/epytope |
| آدرس اینترنتی | https://pypi.org/project/epytope/ |
| مجوز | BSD |
# epytope - An Immunoinformatics Framework for Python
[](https://anaconda.org/bioconda/epytope)
[](https://anaconda.org/bioconda/epytope)
[](https://opensource.org/licenses/BSD-3-Clause)
[](https://anaconda.org/bioconda/epytope)
[](https://anaconda.org/bioconda/epytope)
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.](https://pubmed.ncbi.nlm.nih.gov/15987883/)
- ProteaSMM by [Tenzer et al.](https://pubmed.ncbi.nlm.nih.gov/15868101/)
- [NetChop](https://pubmed.ncbi.nlm.nih.gov/15744535/) 3.1
- Epitope Assembly
- Approach by [Toussaint et al.](https://pubmed.ncbi.nlm.nih.gov/21875632/)
- Bi-objective extension of approach by [Toussaint et al.](https://pubmed.ncbi.nlm.nih.gov/21875632/)
- Assembly with spacers by [Schubert et al.](https://pubmed.ncbi.nlm.nih.gov/26813686/)
- Epitope Prediction
- [SYFPEITHI](https://link.springer.com/article/10.1007/s002510050595)
- [MHCNuggets](https://pubmed.ncbi.nlm.nih.gov/31871119/) 2.0, 2.3.2
- [MHCflurry](https://pubmed.ncbi.nlm.nih.gov/29960884/) 1.2.2, 1.4.3
- [NetMHC](https://pubmed.ncbi.nlm.nih.gov/26515819/) 3.0, 3.4, 4.0
- [NetMHCII](https://pubmed.ncbi.nlm.nih.gov/29315598/) 2.2, 2.3
- [NetMHCpan](https://pubmed.ncbi.nlm.nih.gov/28978689/) 2.4, 2.8, 3.0, 4.0, 4.1
- [NetMHCIIpan](https://pubmed.ncbi.nlm.nih.gov/32406916/) 3.0, 3.1, 4.0, 4.1
- [PickPocket](https://pubmed.ncbi.nlm.nih.gov/19297351/) 1.1
- [NetCTLpan](https://pubmed.ncbi.nlm.nih.gov/20379710/) 1.1
- Epitope Selection
- [OptiTope](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703925/)
- Stability Prediction
- [NetMHCstabpan](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4976001/) 1.0
- TAPP Prediction
- TAP prediction model by [Doytchinova et al.](https://pubmed.ncbi.nlm.nih.gov/15557175/)
- [SMMTAP](https://pubmed.ncbi.nlm.nih.gov/12902473/)
## Getting Started
Users and developers should start by reading our [wiki](https://github.com/KohlbacherLab/epytope/wiki) and [IPython tutorials](https://github.com/KohlbacherLab/epytope/tree/master/epytope/tutorials). A reference documentation is also available [online](http://epytope.readthedocs.org/en/latest/).
## 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](http://bioinformatics.oxfordjournals.org/content/early/2016/02/26/bioinformatics.btw113.short?rss=1)
and the original publications of the used methods.
نیازمندی
| مقدار | نام |
|---|---|
| - | setuptools |
| >=1.3.5 | pandas |
| >=4.0 | pyomo |
| - | PyMySQL |
| - | biopython |
| - | PyVCF3 |
| <=1.4.3 | mhcflurry |
| ==2.3.2 | mhcnuggets |
| <=2.3.1 | keras |
| <=2.10.0 | h5py |
| - | requests |
| - | beautifulsoup4 |
نحوه نصب
نصب پکیج whl epytope-3.3.1:
pip install epytope-3.3.1.whl
نصب پکیج tar.gz epytope-3.3.1:
pip install epytope-3.3.1.tar.gz