ArticleCommunications biology2023
Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling.Nature genetics · 2026Pooled it
- Integrative genetic analysis identifies shared regulation of DNA methylation and gene expression in migraine risk.The journal of headache and pain · 2026Article
- Finding Significant Hits in Networks: a network-based tool for analyzing gene-level P-values to identify significant genes missed by standard methods.Briefings in bioinformatics · 2026Article
- Genome-wide association study for Kleiber ratio and growth efficiency traits in Lori-Bakhtiari sheep.Tropical animal health and production · 2025Article
- Characterizing somatic mutations in ovarian cancer germline risk regions.Communications biology · 2025Article
- Genomic Landscape and Prediction of Udder Traits in Saanen Dairy Goats.Animals : an open access journal from MDPI · 2025Article
- Genetic parameters and QTL mapping for novel metabolic traits in early-lactation Holsteins.Journal of animal science · 2025Article
- Multi-omics cannot replace sample size in genome-wide association studies.Genes, brain, and behavior · 2023Article
- Integrating eQTL and GWAS data characterises established and identifies novel migraine risk loci.Human genetics · 2023Article
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Authors and funding
9 authors.
Funding
Abstract
Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.
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