Nature Communications (Mar 2020)

Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data

  • Haitham Ashoor,
  • Xiaowen Chen,
  • Wojciech Rosikiewicz,
  • Jiahui Wang,
  • Albert Cheng,
  • Ping Wang,
  • Yijun Ruan,
  • Sheng Li

DOI
https://doi.org/10.1038/s41467-020-14974-x
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 11

Abstract

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Accurate identification of sub-compartments from chromatin interaction data remains a challenge. Here, the authors introduce an algorithm combining graph embedding and unsupervised learning to predict sub-compartments using Hi-C data.