Modeling regulatory network topology improves genome-wide analyses of complex human traits
Gene regulatory networks are a useful means of inferring functional interactions from large-scale genomic data. Here, the authors develop a Bayesian framework integrating GWAS summary statistics with gene regulatory networks to identify genetic enrichments and associations simultaneously.
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2021
|
| Subjects: | |
| Online Access: | https://doaj.org/article/3f97afd99a364fa6b7fc3dfd5dfbd711 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Gene regulatory networks are a useful means of inferring functional interactions from large-scale genomic data. Here, the authors develop a Bayesian framework integrating GWAS summary statistics with gene regulatory networks to identify genetic enrichments and associations simultaneously. |
|---|