Abstract
BackgroundDespite the success of genome-wide association studies (GWAS), there still remains “missing heritability” for many traits. One contributing factor may be the result of examining one marker at a time as opposed to a group of markers that are biologically meaningful in aggregate. To address this problem, a variety of gene- and pathway-level methods have been developed to identify putative biologically relevant associations. A simulation was conducted to systematically assess the performance of these methods. Using genetic data from 4,500 individuals in the Wellcome Trust Case Control Consortium (WTCCC), case–control status was simulated based on an additive polygenic model. We evaluated gene-level methods based on their sensitivity, specificity, and proportion of false positives. Pathway-level methods were evaluated on the relationship between proportion of causal genes within the pathway and the strength of association.ResultsThe gene-level methods had low sensitivity (20-63%), high specificity (89-100%), and low proportion of false positives (0.1-6%). The gene-level program VEGAS using only the top 10% of associated single nucleotide polymorphisms (SNPs) within the gene had the highest sensitivity (28.6%) with less than 1% false positives. The performance of the pathway-level methods depended on their reliance upon asymptotic distributions or if significance was estimated in a competitive manner. The pathway-level programs GenGen, GSA-SNP and MAGENTA had the best performance while accounting for potential confounders.ConclusionsNovel genes and pathways can be identified using the gene and pathway-level methods. These methods may provide valuable insight into the “missing heritability” of traits and provide biological interpretations to GWAS findings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0191-2) contains supplementary material, which is available to authorized users.
Highlights
Despite the success of genome-wide association studies (GWAS), there still remains “missing heritability” for many traits
Gene-level analyses A total of 11 methods were evaluated: Fisher’s Combination Test (FCT), Sidak’s Combination Test, Simes’ Test, False Discovery Rate (FDR), Truncated Product Method (TPM), GATES, Hybrid Set-Based Test for Genome-wide Association Studies (HYST), and VEGAS
The proportion of false positives was low at 0.16%
Summary
Despite the success of genome-wide association studies (GWAS), there still remains “missing heritability” for many traits. There remains “missing heritability”, or the discrepancy between the low amounts of within-population phenotypic variation explained by GWAS results and the higher estimates of narrow-sense heritability [2] One explanation for this missing heritability is current studies are underpowered to identify contributing genetic variants. An additional motivation for geneor pathway-level methods is the potential for biologically relevant interpretation as the genes or pathways can be Wojcik et al BMC Genetics (2015) 16:34 selected based on prior knowledge, or in a genome-wide manner. In comparing these programs, many of the issues surrounding these analytical methods are similar, the underlying hypotheses and limitations may be distinct
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