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.
Guardado en:
Autores principales: | Long Gao, Yasin Uzun, Peng Gao, Bing He, Xiaoke Ma, Jiahui Wang, Shizhong Han, Kai Tan |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/5472bfb79e7346c78601c129c375ba8e |
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