eNet: an algorithm to build enhancer networks based on scATAC-seq and scRNA-seq data

Introduction

eNet is an algorithm designed to integrate single-cell chromatin accessibility and gene expression profiles and build enhancer networks, delineating how multiple enhancers interact with each other in gene regulation.

Workflow

See https://github.com/xmuhuanglab/eNet/blob/main/R/README.md for more detailed tutorial.

How to cite eNet

1. Danni Hong#, Hongli Lin#, Lifang Liu, Muya Shu, Jianwu Dai, Falong Lu, Jialiang Huang*. Complexity of enhancer networks predicts cell identity and disease genes. (Submitted)
2. Muya Shu#, Danni Hong#, Hongli Lin, Jixiang Zhang, Zhengnan Luo, Yi Du, Zheng Sun, Man Yin, Yanyun Yin, Shilai Bao, Zhiyong Liu, Falong Lu*, Jialiang Huang*, Jianwu Dai*. Enhancer networks driving mouse spinal cord development revealed by single-cell multi-omics analysis. (Submitted)