All SNPs Are Not Created Equal: Genome-Wide Association Studies Reveal a Consistent Pattern of Enrichment among Functionally Annotated SNPs
By A. Schork, W. Thompson, Phillip H. Pham, Ali Torkamani, J. Roddey, Patrick F. Sullivan, J. Kelsoe, M. O’Donovan, H. Furberg, N. Schork and 2 more. PLoS Genetics, 2013
310 citations recorded by the source corpus.
Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci.
Subfields: Genetics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/a77031db15da51114bae7f1b972ca255994f0677
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
In Molecular Biology
Citations in the corpus
- Polygenic scores via penalized regression on summary statistics (2016, background): “Likewise additional information gained in the consideration of functional annotations of the genome (Schork et al., 2013; Pickrell, 2014; Kichaev et al., 2014) can be incorporated similarly.”