ArticleNature computational science2025
Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.
Article in Nature computational science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Distinct patterns of genetic overlap among multimorbidities revealed with trivariate MiXeR.Genome medicine · 2025Article
- Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.Nature computational science · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The cost of recruiting participants for genome-wide association studies (GWASs) can limit sample sizes and hinder the discovery of genetic variants. Here we introduce the surrogate functional false discovery rate (sfFDR) framework that integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q value, and uses these estimates to derive a functional P value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses. Compared with a standard analysis, sfFDR substantially increased power (equivalent to a 52% increase in sample size) in a study of obesity-related traits from the UK Biobank and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.