QuickStart
========================



Introduction to DeepChrInteract
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Though deep learning methods have been widely developed for predicting chromatin interactions using flanking DNA sequence in identified chromatin interaction regions, 
a comprehensive software toolkit to integrate and evaluate different deep learning architectures are under-developed. 
By adopting different feature representation for flanking DNA sequence as well as different neural network architectures, 
we present DeepChrInteract (Deep learning for predicting Chromatin Interactions), which is a Python toolkit that offers representative deep learning methods to predict genome-wide chromatin interactions.

System Requirements
+++++++++++++++++++

- CPU memory is recommended as ``16GB``
- GPU memory is recommended as ``8GB``
- Python 3.8
- Keras == 2.4.0
- TensorFlow == 2.3.0
- numpy >= 1.15.4
- scipy >= 1.2.1
- scikit-learn >= 0.20.3
- seaborn >=0.9.0
- matplotlib >=3.1.0



Download
++++++++

git clone https://github.com/lichen-lab/DeepChrInteract



Maintainer
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- Ziqian Bi (bizi@iu.edu)
- Li Chen (chen61@iu.edu)




.. image:: img/div.png