Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics
University College London · Murdoch Children's Research Institute · +8 more institutions
Abstract
Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair…
Citation impact
- FWCI
- 34.65
- Percentile
- 100%
- References
- 70
Authors
7- CGClaudia GiambartolomeiCorresponding
University College London
- DVDamjan Vukcevic
Murdoch Children's Research Institute, Royal Children's Hospital
- EEEric E. Schadt
Icahn School of Medicine at Mount Sinai
- LFLude Franke
University Medical Center Groningen, University of Groningen
- ADAroon D. Hingorani
University College London
Topics & keywords
- Expression quantitative trait loci
- Genome-wide association study
- Biology
- Genetic association
- Quantitative trait locus
- Computational biology
- SNP
- Genetics
Funding
- WTWellcome TrustAwards: 091157, 100140
- NINational Institute for Health and Care Research
- BHBritish Heart Foundation
- MEMoorfields Eye Hospital NHS Foundation Trust
- MRMedical Research CouncilAward: MR/K006584/1
- CICambridge Institute for Medical Research, University of CambridgeAward: 100140
- NCNIHR Cambridge Biomedical Research Centre