ReviewGenetics research2010
Statistical analysis of genetic interactions.
Review in Genetics research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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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
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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-Wide Interaction Analyses of Serum Calcium on Ventricular Repolarization Time in 125 393 Participants.Journal of the American Heart Association · 2024Pooled it
- Biomedical literature mining: graph kernel-based learning for gene-gene interaction extraction.European journal of medical research · 2024Article
- Gene-Gene Interaction Between Factor-Neurology · 2024Article
- A global genetic interaction network by single-cell imaging and machine learning.Cell systems · 2023Article
- Sweet Taste Receptor Gene and Caries Trajectory in the Life Course.Journal of dental research · 2023Article
- Machine Learning to Identify Interaction of Single-Nucleotide Polymorphisms as a Risk Factor for Chronic Drug-Induced Liver Injury.International journal of environmental research and public health · 2021Article
- Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications.International journal of molecular sciences · 2020Article
- Genome-wide association and epistatic interactions of flowering time in soybean cultivar.PloS one · 2020Article
- Bayesian hierarchical modelling for inferring genetic interactions in yeast.Journal of the Royal Statistical Society. Series C, Applied statistics · 2016Article
- EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.Frontiers in genetics · 2016Article
- Article
- SIRT6 minor allele genotype is associated with >5-year decrease in lifespan in an aged cohort.PloS one · 2014Article
- Genetic screening for the risk of type 2 diabetes: worthless or valuable?Diabetes care · 2013Review
- Gene-alcohol interactions identify several novel blood pressure loci including a promising locus near SLC16A9.Frontiers in genetics · 2013Article
- Exploiting gene expression variation to capture gene-environment interactions for disease.Frontiers in genetics · 2012Article
- Hierarchical generalized linear models for multiple groups of rare and common variants: jointly estimating group and individual-variant effects.PLoS genetics · 2011Article
- The role of the fat mass and obesity associated gene (FTO) in breast cancer risk.BMC medical genetics · 2011Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
Many common human diseases and complex traits are highly heritable and influenced by multiple genetic and environmental factors. Although genome-wide association studies (GWAS) have successfully identified many disease-associated variants, these genetic variants explain only a small proportion of the heritability of most complex diseases. Genetic interactions (gene-gene and gene-environment) substantially contribute to complex traits and diseases and could be one of the main sources of the missing heritability. This paper provides an overview of the available statistical methods and related computer software for identifying genetic interactions in animal and plant experimental crosses and human genetic association studies. The main discussion falls under the three broad issues in statistical analysis of genetic interactions: the definition, detection and interpretation of genetic interactions. Recently developed methods based on modern techniques for high-dimensional data are reviewed, including penalized likelihood approaches and hierarchical models; the relationships between these methods are also discussed. I conclude this review by highlighting some areas of future research.
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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.