ArticleJournal of the American Statistical Association2017
Sparse simultaneous signal detection for identifying genetically controlled disease genes.
Article in Journal of the American Statistical Association, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
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Who cites it
3 citing papers in PubMed.
- Multi-trait association studies discover pleiotropic loci between Alzheimer's disease and cardiometabolic traits.Alzheimer's research & therapy · 2021Article
- A statistical framework for cross-tissue transcriptome-wide association analysis.Nature genetics · 2019Article
- Optimal detection of weak positive latent dependence between two sequences of multiple tests.Journal of multivariate analysis · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Genome-wide association studies (GWAS) and differential expression analyses have had limited success in finding genes that cause complex diseases such as heart failure (HF), a leading cause of death in the United States. This paper proposes a new statistical approach that integrates GWAS and expression quantitative trait loci (eQTL) data to identify important HF genes. For such genes, genetic variations that perturb its expression are also likely to influence disease risk. The proposed method thus tests for the presence of simultaneous signals: SNPs that are associated with the gene's expression as well as with disease. An analytic expression for the
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Registered trials
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