Author:
Svishcheva Gulnara R.,Tiys Evgeny S.,Elgaeva Elizaveta E.,Feoktistova Sofia G.,Timmers Paul R. H. J.,Sharapov Sodbo Zh.,Axenovich Tatiana I.,Tsepilov Yakov A.
Abstract
AbstractWe propose a novel effective framework for analysis of the shared genetic background for a set of genetically correlated traits using SNP-level GWAS summary statistics. This framework called SHAHER is based on the construction of a linear combination of traits by maximizing the proportion of its genetic variance explained by the shared genetic factors. SHAHER requires only full GWAS summary statistics and matrices of genetic and phenotypic correlations between traits as inputs. Our framework allows both shared and unshared genetic factors to be to effectively analyzed. We tested our framework using simulation studies, compared it with previous developments, and assessed its performance using three real datasets: anthropometric traits, psychiatric conditions and lipid concentrations. SHAHER is versatile and applicable to summary statistics from GWASs with arbitrary sample sizes and sample overlaps, allows incorporation of different GWAS models (Cox, linear and logistic) and is computationally fast.
Publisher
Cold Spring Harbor Laboratory
Reference25 articles.
1. Shared heritability and functional enrichment across six solid cancers;Nature communications,2019
2. Control of protein palmitoylation by regulating substrate recruitment to a zDHHC-protein acyltransferase
3. Sampson JN , Wheeler WA , Yeager M , Panagiotou O , Wang Z , Berndt SI , et al. Analysis of heritability and shared heritability based on genome-wide association studies for 13 cancer types. JNCI: Journal of the National Cancer Institute. 2015;107(12).
4. Analysis of shared heritability in common disorders of the brain
5. Shared genetic factors underlie migraine and depression;Twin Research and Human Genetics,2016