ArticleScientific reports2013
An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers, 1 of them a synthesis that pooled it.
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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.
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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.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci.Nature genetics · 2016Pooled it
- Analysis of gene-gene interactions among common variants in candidate cardiovascular genes in coronary artery disease.PloS one · 2015Trial
- A prototype-augmented graph representation learning framework for identifying brain disorder-associated genes and facilitating drug repurposing.PLoS computational biology · 2026Article
- Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models.ArXiv · 2025Article
- ACOCMPMI: An Ant Colony Optimization Algorithm Based on Composite Multiscale Part Mutual Information for Detecting Epistatic Interactions.Human mutation · 2025Article
- Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Considerations in the search for epistasis.Genome biology · 2024Review
- Assessing the limitations of relief-based algorithms in detecting higher-order interactions.BioData mining · 2024Article
- Network medicine-based epistasis detection in complex diseases: ready for quantum computing.Nucleic acids research · 2024Article
- Network medicine-based epistasis detection in complex diseases: ready for quantum computing.medRxiv : the preprint server for health sciences · 2023Article
- Transcriptome-wide gene-gene interaction associations elucidate pathways and functional enrichment of complex traits.PLoS genetics · 2023Article
- Interpreting coronary artery disease GWAS results: A functional genomics approach assessing biological significance.PloS one · 2022Article
- Identification of genetic risk loci for depression and migraine comorbidity in Han Chinese residing in Taiwan.Frontiers in psychiatry · 2022Article
- DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies.NAR genomics and bioinformatics · 2021Article
- Large-scale genome-wide association study, using historical data, identifies conserved genetic architecture of cyanogenic glucoside content in cassava (Manihot esculenta Crantz) root.The Plant journal : for cell and molecular biology · 2021Article
- A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions.BioData mining · 2021Article
- Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies.BMC bioinformatics · 2019Article
- Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.Journal of experimental botany · 2019Article
- Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data.Scientific reports · 2019Article
- Multiple Epistasis Interactions Within MHC Are Associated With Ulcerative Colitis.Frontiers in genetics · 2019Article
Corrections and comments
- Erratum issuedPoong, Hoifung [corrected to Poon, Hoifung]
Authors and funding
8 authors.
Funding
Abstract
We present an approach for genome-wide association analysis with improved power on the Wellcome Trust data consisting of seven common phenotypes and shared controls. We achieved improved power by expanding the control set to include other disease cohorts, multiple races, and closely related individuals. Within this setting, we conducted exhaustive univariate and epistatic interaction association analyses. Use of the expanded control set identified more known associations with Crohn's disease and potential new biology, including several plausible epistatic interactions in several diseases. Our work suggests that carefully combining data from large repositories could reveal many new biological insights through increased power. As a community resource, all results have been made available through an interactive web server.
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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 OpenQuestion graph.