Fast and powerful genome wide association of dense genetic data with high dimensional imaging phenotypes
Genome-wide association studies (GWAS) of neuroimaging data pose a significant computational burden because of the need to correct for multiple testing in both the genetic and the imaging data. Here, Ganjgahi et al. develop WLS-REML which significantly reduces computation running times in brain imag...
Enregistré dans:
| Auteurs principaux: | , , , , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/3315ced0f5074d3a9344c50e4a584c44 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|