Identifying noncoding risk variants using disease-relevant gene regulatory networks
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.
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2018-02-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-018-03133-y |