ArticleGenetic epidemiology2009
The challenge of detecting epistasis (G x G interactions): Genetic Analysis Workshop 16.
Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.bioRxiv : the preprint server for biology · 2024Article
- Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.Virus evolution · 2024Article
- A Case for Returning to Multiplex Families for Further Understanding the Heritability of Schizophrenia: A Psychiatrist's Perspective.Molecular neuropsychiatry · 2016Article
- A Framework for Interpreting Type I Error Rates from a Product-Term Model of Interaction Applied to Quantitative Traits.Genetic epidemiology · 2016Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
- Genotype-environment interactions for quantitative traits in Korea Associated Resource (KARE) cohorts.BMC genetics · 2014Article
- Construction and analysis of single nucleotide polymorphism-single nucleotide polymorphism interaction networks.IET systems biology · 2013Article
- Association of genetic variation with gene expression and protein abundance within the natriuretic peptide pathway.Journal of cardiovascular translational research · 2013Article
- Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2.BMC bioinformatics · 2012Article
- Systematic detection of epistatic interactions based on allele pair frequencies.PLoS genetics · 2012Article
- Modeling haplotype-haplotype interactions in case-control genetic association studies.Frontiers in genetics · 2012Article
- A novel statistic for genome-wide interaction analysis.PLoS genetics · 2010Article
- Dissecting the genetic architecture of host-pathogen specificity.PLoS pathogens · 2010Article
- Genome-wide association studies for discrete traits.Genetic epidemiology · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.
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.