SNAF

KO | EN

gitlite — search

#javascript #hacktoberfest #react #android #machine-learning #deep-learning #linux #macos #awesome #awesome-list #pytorch #mcp #ios #openai

(★ 55)

Splicing Neo Antigen Finder (SNAF) is an easy-to-use Python package to identify splicing-derived tumor neoantigens from RNA sequencing data, it further leverages both deep learning and hierarchical Bayesian models to prioritize certain candidates for experimental validation

SNAF 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

[![Documentation Status](https://readthedocs.org/projects/snaf/badge/?version=latest)](https://snaf.readthedocs.io/en/latest/?badge=latest)  [![Pypi](https://img.shields.io/pypi/v/snaf?logo=PyPI)](https://pypi.org/project/snaf/)  [![Downloads](https://pepy.tech/badge/snaf)](https://pypi.org/project/snaf/)  [![Stars](https://img.shields.io/github/stars/frankligy/SNAF)](https://github.com/frankligy/SNAF/stargazers)

# SNAF
Splicing Neo Antigen Finder (SNAF) is an easy-to-use Python package to identify splicing-derived tumor neoantigens from RNA sequencing data, it can 
predict, prioritize and visualize MHC-bound neoantigen for T cell (T antigen) and altered surface protein for B cell (B antigen).

![workflow](https://raw.githubusercontent.com/frankligy/SNAF/main/images/fig1.png)

# Tutorial and documentation

See [Full Documentation](https://snaf.readthedocs.io).

Particulary, to avoid hassle, it is advisable to start a `fresh conda environment` with `python 3.7` on a `Linux system`, and use this specific git commit (I am actively
maintaining it) instead of the stable pypi version.

```bash
pip install git+https://github.com/frankligy/SNAF.git@e23ce39512a1a7f58c74e59b4b7cedc89248b908
```

# Interactive Viewers (below, take a few seconds to load)

# Input and Output

Simply put, user needs to supply ``a folder with bam files``, and the ``HLA type`` assciated with each patient (using your favorite HLA typing tool). And it will generate predicted immunogenic MHC-bound peptides and altered surface protein. Moreover, there's a myriad of convenient function that enables users to conduct survival analysis, association analysis and publication-quality visualiztion. Check our tutorials for more detail.

# Auxiliary Programs developed within SNAF

- [RNA-SPRINT](https://github.com/frankligy/SNAF/tree/main/RNA-SPRINT): Infering splicing factor activity from RNA-Seq.

- [BayesTS](https://github.com/frankligy/BayesTS): BayesTS can infer tumor specificity for any features (gene, protein, splicing junction, etc).

- [DeepImmuno](https://github.com/frankligy/DeepImmuno): DeepImmuno can infer immunogenicity for peptide-MHC complex.

# Citation

Guangyuan Li et al. ,Splicing neoantigen discovery with SNAF reveals shared targets for cancer immunotherapy.Sci. Transl. Med.16,eade2886(2024).DOI:10.1126/scitranslmed.ade2886 (https://www.science.org/doi/10.1126/scitranslmed.ade2886)

# Contact

Guangyuan(Frank) Li

Email: li2g2@mail.uc.edu

PhD student, Biomedical Informatics

Cincinnati Children’s Hospital Medical Center(CCHMC)

University of Cincinnati, College of Medicine

SNAF

SNAF 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

SNAF

SNAF 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README