ReviewAnnals of human genetics2011
Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.
Review in Annals of human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
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
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Multiple associated variants increase the heritability explained for plasma lipids and coronary artery disease.Circulation. Cardiovascular genetics · 2014Pooled it
- ACOCMPMI: An Ant Colony Optimization Algorithm Based on Composite Multiscale Part Mutual Information for Detecting Epistatic Interactions.Human mutation · 2025Article
- Missing Causality and Heritability of Autoimmune Hepatitis.Digestive diseases and sciences · 2023Article
- Genetic heterogeneity: Challenges, impacts, and methods through an associative lens.Genetic epidemiology · 2022Review
- RIL-StEp: epistasis analysis of rice recombinant inbred lines reveals candidate interacting genes that control seed hull color and leaf chlorophyll content.G3 (Bethesda, Md.) · 2021Article
- What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?Journal of personalized medicine · 2020Review
- Article
- How to increase our belief in discovered statistical interactions via large-scale association studies?Human genetics · 2019Review
- A Low Resolution Epistasis Mapping Approach To Identify Chromosome Arm Interactions in Allohexaploid Wheat.G3 (Bethesda, Md.) · 2019Article
- Epistasis detectably alters correlations between genomic sites in a narrow parameter window.PloS one · 2019Article
- Candidate Variants for Additive and Interactive Effects on Bioenergy Traits in Switchgrass (The plant genome · 2018Article
- Evolutionary footprint of epistasis.PLoS computational biology · 2018Article
- The search for gene-gene interactions in genome-wide association studies: challenges in abundance of methods, practical considerations, and biological interpretation.Annals of translational medicine · 2018Article
- Identifying gene-gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts.Human genetics · 2017Article
- Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases.BioData mining · 2017Article
- Reverse Pathway Genetic Approach Identifies Epistasis in Autism Spectrum Disorders.PLoS genetics · 2017Article
- Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium.PLoS genetics · 2016Article
- PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2016Article
- Biology-Driven Gene-Gene Interaction Analysis of Age-Related Cataract in the eMERGE Network.Genetic epidemiology · 2015Article
- A random forest approach to capture genetic effects in the presence of population structure.Nature communications · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The search for the missing heritability in genome-wide association studies (GWAS) has become an important focus for the human genetics community. One suspected location of these genetic effects is in gene-gene interactions, or epistasis. The computational burden of exploring gene-gene interactions in the wealth of data generated in GWAS, along with small to moderate sample sizes, have led to epistasis being an afterthought, rather than a primary focus of GWAS analyses. In this review, I discuss some potential approaches to filter a GWAS dataset to a smaller, more manageable dataset where searching for epistasis is considerably more feasible. I describe a number of alternative approaches, but primarily focus on the use of prior biological knowledge from databases in the public domain to guide the search for epistasis. The manner in which prior knowledge is incorporated into a GWA study can be many and these data can be extracted from a variety of database sources. I discuss a number of these approaches and propose that a comprehensive approach will likely be most fruitful for searching for epistasis in large-scale genomic studies of the current state-of-the-art and into the future.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.