PuSH - Publication Server of Helmholtz Zentrum München

Rivas, M.A.* ; Pirinen, M.* ; Neville, M.J.* ; Gaulton, K.J.* ; Moutsianas, L.* ; GoT2D Consortium (Gieger, C. ; Grallert, H. ; Hrabě de Angelis, M. ; Huth, C. ; Kriebel, J. ; Meisinger, C. ; Meitinger, T. ; Müller-Nurasyid, M. ; Peters, A. ; Rathmann, W. ; Ried, J.S. ; Strauch, K. ; Donnelly, P.) ; Lindgren, C.M.* ; Karpe, F.* ; McCarthy, M.I.*

Assessing association between protein truncating variants and quantitative traits.

Bioinformatics 29, 2419-2426 (2013)
Publ. Version/Full Text DOI PMC
Free by publisher
Creative Commons Lizenzvertrag
Open Access Green as soon as Postprint is submitted to ZB.
MOTIVATION: In sequencing studies of common diseases and quantitative traits, power to test rare and low frequency variants individually is weak. To improve power, a common approach is to combine statistical evidence from several genetic variants in a region. Major challenges are how to do the combining and which statistical framework to use. General approaches for testing association between rare variants and quantitative traits include aggregating genotypes and trait values, referred to as 'collapsing', or using a score-based variance component test. However, little attention has been paid to alternative models tailored for protein truncating variants. Recent studies have highlighted the important role that protein truncating variants, commonly referred to as 'loss of function' variants, may have on disease susceptibility and quantitative levels of biomarkers. We propose a Bayesian modelling framework for the analysis of protein truncating variants and quantitative traits. RESULTS: Our simulation results show that our models have an advantage over the commonly used methods. We apply our models to sequence and exome-array data and discover strong evidence of association between low plasma triglyceride levels and protein truncating variants at APOC3 (Apolipoprotein C3). AVAILABILITY: Software is available from http://www.well.ox.ac.uk/~rivas/mamba
Altmetric
Additional Metrics?
[➜Log in]
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
ISSN (print) / ISBN 1367-4803
Journal Bioinformatics
Quellenangaben Volume: 29, Issue: 19, Pages: 2419-2426 Article Number: , Supplement: ,
Publisher Oxford University Press
Publishing Place Oxford
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Genetic Epidemiology (IGE)
Institute of Human Genetics (IHG)
Institute of Experimental Genetics (IEG)
Institute of Epidemiology II (EPI2)