Metadata-Version: 2.1
Name: SNAF
Version: 0.5.0
Summary: A Python package to predict, prioritize and visualize splicing derived neoantigens, including MHC-bound peptides (T cell antigen) and altered surface protein (B cell antigen)
Home-page: https://github.com/frankligy/SNAF
Author: Guangyuan(Frank) Li
Author-email: li2g2@mail.uc.edu
Maintainer: Guangyuan(Frank) Li
Maintainer-email: li2g2@mail.uc.edu
License: UNKNOWN
Project-URL: Documentation, https://snaf.readthedocs.io
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: tensorflow (==2.3.0)
Requires-Dist: pandas (==1.3.4)
Requires-Dist: numpy (==1.18.5)
Requires-Dist: numba (==0.53.0)
Requires-Dist: mhcflurry (==2.0.5)
Requires-Dist: h5py (==2.10.0)
Requires-Dist: anndata (==0.7.6)
Requires-Dist: seaborn (==0.11.2)
Requires-Dist: biopython (==1.79)
Requires-Dist: requests (==2.26.0)
Requires-Dist: xmltodict (==0.12.0)
Requires-Dist: xmltramp2 (==3.1.1)
Requires-Dist: tqdm (==4.62.3)
Requires-Dist: scipy (==1.4.1)
Requires-Dist: statsmodels (==0.13.1)
Requires-Dist: lifelines (==0.26.4)
Requires-Dist: umap-learn (==0.5.2)
Requires-Dist: plotly (==5.4.0)
Requires-Dist: dash (==2.0.0)
Requires-Dist: dash-dangerously-set-inner-html (==0.0.2)
Requires-Dist: mygene (==3.2.2)

# SNAF
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 validations

## Environments

```bash
conda create -n neo_env python=3.7
pip install tensorflow==2.3.0 pandas==1.1.1 numpy==1.18.5
pip install h5py anndata matplotlib seaborn requests xmltodict tqdm
conda install -c conda-forge pymc3 mkl-service   # numpy will be updated to 1.21.3 (seems not, still 1.18.5)
pip install mhcflurry==2.0.5 # for now version seems to not matter
pip install statsmodels lifelines umap plotly   # numba needs to be 0.53
pip install requests xmltramp2 dash-dangerously-set-inner-html
pip install mygene
```


