Nature Communications (Feb 2018)

Identifying noncoding risk variants using disease-relevant gene regulatory networks

  • Long Gao,
  • Yasin Uzun,
  • Peng Gao,
  • Bing He,
  • Xiaoke Ma,
  • Jiahui Wang,
  • Shizhong Han,
  • Kai Tan

DOI
https://doi.org/10.1038/s41467-018-03133-y
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 12

Abstract

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Current methods for prioritization of non-coding genetic risk variants are based on sequence and chromatin features. Here, Gao et al. develop ARVIN, which predicts causal regulatory variants using disease-relevant gene-regulatory networks, and validate this approach in reporter gene assays.