Metadata-Version: 2.1
Name: bio-gopher
Version: 1.0.2
Summary: GOPHER: GenOmic Profile-model compreHensive EvaluatoR
Author-email: Shushan Toneyan <toneyan@cshl.edu>, Ziqi Tang <ztang@cshl.edu>, Peter Koo <pkoo@cshl.edu>
Project-URL: Homepage, https://github.com/shtoneyan/gopher
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE


<img src="./DALL·E 2022-10-05 14.40.17 - Constellation in a shape of groundhog. graphical art.png" width="100" height='100'>

**GOPHER**: **G**en**O**mic **P**rofile-model compre**H**ensive **E**valuato**R**

## Installation

```
$ pip install bio-gopher
```

This repository contains scripts for data preprocessing, training deep learning models for DNA sequence to epigenetic function prediction and evaluation of models.

The repo contains a set of tutorial jupyter notebooks that illustrate these steps on a toy dataset. The two notebooks below are required prerequisites for the rest of tutorials:
- preprocessing/preprocessing/quant_dataset_tutorial.ipynb
- tutorials/train_model.ipynb


To replicate the results of the manuscript run the scripts in the analyzis directory. As a prerequisite download and unzip dataset.zip, trained_models.zip from zenodo https://doi.org/10.5281/zenodo.6464031 within the git repo. These contain test sets and pre-trained models. The analysis scripts can be ran in any order as long as paper_run_evaluate.py is ran first, in order to produce model evaluations which is required for further steps.
