ArticleBioinformatics (Oxford, England)2016
Adaptive gene- and pathway-trait association testing with GWAS summary statistics.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
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Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A gene based combination test using GWAS summary data.BMC bioinformatics · 2023Pooled it
- Discovery and fine-mapping of loci associated with MUFAs through trans-ethnic meta-analysis in Chinese and European populations.Journal of lipid research · 2017Pooled it
- Genetic risk predictions using deep learning models with summary data.Frontiers in bioinformatics · 2025Article
- Leveraging multimodal neuroimaging and GWAS for identifying modality-level causal pathways to Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Gene-based association tests in family samples using GWAS summary statistics.Genetic epidemiology · 2024Article
- Hierarchical association of COPD to principal genetic components of biological systems.PloS one · 2023Article
- A comprehensive comparison of multilocus association methods with summary statistics in genome-wide association studies.BMC bioinformatics · 2022Article
- Gene-based association tests using GWAS summary statistics and incorporating eQTL.Scientific reports · 2022Article
- Speeding up Monte Carlo simulations for the adaptive sum of powered score test with importance sampling.Biometrics · 2022Article
- Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis.Frontiers in genetics · 2022Article
- A Novel Hierarchical Clustering Approach for Joint Analysis of Multiple Phenotypes Uncovers Obesity Variants Based on ARIC.Frontiers in genetics · 2022Article
- Genetic dissection of complex traits using hierarchical biological knowledge.PLoS computational biology · 2021Article
- Integrating brain imaging endophenotypes with GWAS for Alzheimer's disease.Quantitative biology (Beijing, China) · 2021Article
- A Novel Approach Integrating Hierarchical Clustering and Weighted Combination for Association Study of Multiple Phenotypes and a Genetic Variant.Frontiers in genetics · 2021Article
- Integrating comprehensive functional annotations to boost power and accuracy in gene-based association analysis.PLoS genetics · 2020Article
- Article
- TS: a powerful truncated test to detect novel disease associated genes using publicly available gWAS summary data.BMC bioinformatics · 2020Article
- A Bayesian hierarchical variable selection prior for pathway-based GWAS using summary statistics.Statistics in medicine · 2020Article
- A powerful fine-mapping method for transcriptome-wide association studies.Human genetics · 2020Article
- PAST: The Pathway Association Studies Tool to Infer Biological Meaning from GWAS Datasets.Plants (Basel, Switzerland) · 2020Article
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2 authors.
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Abstract
backgroundGene- and pathway-based analyses offer a useful alternative and complement to the usual single SNP-based analysis for GWAS. On the other hand, most existing gene- and pathway-based tests are not highly adaptive, and/or require the availability of individual-level genotype and phenotype data. It would be desirable to have highly adaptive tests applicable to summary statistics for single SNPs. This has become increasingly important given the popularity of large-scale meta-analyses of multiple GWASs and the practical availability of either single GWAS or meta-analyzed GWAS summary statistics for single SNPs.
resultsWe extend two adaptive tests for gene- and pathway-level association with a univariate trait to the case with GWAS summary statistics without individual-level genotype and phenotype data. We use the WTCCC GWAS data to evaluate and compare the proposed methods and several existing methods. We further illustrate their applications to a meta-analyzed dataset to identify genes and pathways associated with blood pressure, demonstrating the potential usefulness of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.