ArticleThe annals of applied statistics2014
JOINT ANALYSIS OF SNP AND GENE EXPRESSION DATA IN GENETIC ASSOCIATION STUDIES OF COMPLEX DISEASES.
Article in The annals of applied statistics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.
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Who cites it
61 citing papers in PubMed, 1 synthesis or guideline pooled it, 89 citations in OpenAlex.
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- Biomarker interaction selection and disease detection based on multivariate gain ratio.BMC bioinformatics · 2022Article
- Varying Coefficient Mediation Model and Application to Analysis of Behavioral Economics Data.Journal of business & economic statistics : a publication of the American Statistical Association · 2022Article
- The role of ideation on the effect of an SBC intervention on consistent bed net use among caregivers of children under 5 years in Nigeria: a multilevel mediation analysis.BMC public health · 2021Article
- Application of Nanotechnology for Sensitive Detection of Low-Abundance Single-Nucleotide Variations in Genomic DNA: A Review.Nanomaterials (Basel, Switzerland) · 2021Review
- Discover novel disease-associated genes based on regulatory networks of long-range chromatin interactions.Methods (San Diego, Calif.) · 2021Article
- A Correlation Analysis between SNPs and ROIs of Alzheimer's Disease Based on Deep Learning.BioMed research international · 2021Article
- A general framework for integrative analysis of incomplete multiomics data.Genetic epidemiology · 2020Article
- Estimation and inference for the indirect effect in high-dimensional linear mediation models.Biometrika · 2020Article
1 more citing papers are in PubMed but not listed here.
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3 authors at 2 institutions in 1 country.
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Abstract
Genetic association studies have been a popular approach for assessing the association between common Single Nucleotide Polymorphisms (SNPs) and complex diseases. However, other genomic data involved in the mechanism from SNPs to disease, e.g., gene expressions, are usually neglected in these association studies. In this paper, we propose to exploit gene expression information to more powerfully test the association between SNPs and diseases by jointly modeling the relations among SNPs, gene expressions and diseases. We propose a variance component test for the total effect of SNPs and a gene expression on disease risk. We cast the test within the causal mediation analysis framework with the gene expression as a potential mediator. For eQTL SNPs, the use of gene expression information can enhance power to test for the total effect of a SNP-set, which are the combined direct and indirect effects of the SNPs mediated through the gene expression, on disease risk. We show that the test statistic under the null hypothesis follows a mixture of
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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 OpenQuestion graph.