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 Portfolio
2018-02-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-018-03133-y |
| _version_ | 1818992607660867584 |
|---|---|
| author | Long Gao Yasin Uzun Peng Gao Bing He Xiaoke Ma Jiahui Wang Shizhong Han Kai Tan |
| author_facet | Long Gao Yasin Uzun Peng Gao Bing He Xiaoke Ma Jiahui Wang Shizhong Han Kai Tan |
| author_sort | Long Gao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T20:28:51Z |
| format | Article |
| id | doaj.art-5472bfb79e7346c78601c129c375ba8e |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-20T20:28:51Z |
| publishDate | 2018-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-5472bfb79e7346c78601c129c375ba8e2022-12-21T19:27:24ZengNature PortfolioNature Communications2041-17232018-02-019111210.1038/s41467-018-03133-yIdentifying noncoding risk variants using disease-relevant gene regulatory networksLong Gao0Yasin Uzun1Peng Gao2Bing He3Xiaoke Ma4Jiahui Wang5Shizhong Han6Kai Tan7Department of Genetics, Perelman School of Medicine, University of PennsylvaniaDivision of Oncology and Center for Childhood Cancer Research, Children’s Hospital of PhiladelphiaDivision of Oncology and Center for Childhood Cancer Research, Children’s Hospital of PhiladelphiaDivision of Oncology and Center for Childhood Cancer Research, Children’s Hospital of PhiladelphiaSchool of Computer Science and Technology, Xidian UniversityThe Jackson LaboratoryDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of MedicineDepartment of Genetics, Perelman School of Medicine, University of PennsylvaniaCurrent 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.https://doi.org/10.1038/s41467-018-03133-y |
| spellingShingle | Long Gao Yasin Uzun Peng Gao Bing He Xiaoke Ma Jiahui Wang Shizhong Han Kai Tan Identifying noncoding risk variants using disease-relevant gene regulatory networks Nature Communications |
| title | Identifying noncoding risk variants using disease-relevant gene regulatory networks |
| title_full | Identifying noncoding risk variants using disease-relevant gene regulatory networks |
| title_fullStr | Identifying noncoding risk variants using disease-relevant gene regulatory networks |
| title_full_unstemmed | Identifying noncoding risk variants using disease-relevant gene regulatory networks |
| title_short | Identifying noncoding risk variants using disease-relevant gene regulatory networks |
| title_sort | identifying noncoding risk variants using disease relevant gene regulatory networks |
| url | https://doi.org/10.1038/s41467-018-03133-y |
| work_keys_str_mv | AT longgao identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT yasinuzun identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT penggao identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT binghe identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT xiaokema identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT jiahuiwang identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT shizhonghan identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks AT kaitan identifyingnoncodingriskvariantsusingdiseaserelevantgeneregulatorynetworks |