QuickStart¶
Introduction to DeepChrInteract¶
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
16GBGPU memory is recommended as
8GBPython 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¶
Maintainer¶
Ziqian Bi (bizi@iu.edu)
Li Chen (chen61@iu.edu)
