Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories
Identifying associations of rare variants with disease is challenging due to small effect sizes, technical artefacts and population structure heterogeneity. Here, the authors present RV-EXCALIBER, a method that uses large summary-level exome data to robustly calibrate rare variant burden.
Saved in:
Main Authors: | Ricky Lali, Michael Chong, Arghavan Omidi, Pedrum Mohammadi-Shemirani, Ann Le, Edward Cui, Guillaume Paré |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/a1bacb5072a44cb987a5aa7ca05c17bd |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rare variants in ischemic stroke: an exome pilot study.
by: John W Cole, et al.
Published: (2012) -
Large-scale whole-exome sequencing association studies identify rare functional variants influencing serum urate levels
by: Adrienne Tin, et al.
Published: (2018) -
Whole-exome sequencing identifies common and rare variant metabolic QTLs in a Middle Eastern population
by: Noha A. Yousri, et al.
Published: (2018) -
Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts
by: Elizabeth T. Cirulli, et al.
Published: (2020) -
Contextualizing genetic risk score for disease screening and rare variant discovery
by: Dan Zhou, et al.
Published: (2021)