ArticleBMC bioinformatics2009
Detecting disease-associated genotype patterns.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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
13 citing papers in PubMed.
- Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach.BMC bioinformatics · 2022Article
- Leveraging Mann-Whitney U test on large-scale genetic variation data for analysing malaria genetic markers.Malaria journal · 2022Article
- Detecting gene-gene interactions for complex quantitative traits using generalized fuzzy classification.BMC bioinformatics · 2018Article
- AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.PLoS computational biology · 2014Article
- Extensive ethnogenomic diversity of endothelial nitric oxide synthase (eNOS) polymorphisms.Gene regulation and systems biology · 2013Article
- Identifying interacting genetic variations by fish-swarm logic regression.BioMed research international · 2013Article
- A Polygenic Approach to the Study of Polygenic Diseases.Acta naturae · 2012Article
- Genotype patterns at PICALM, CR1, BIN1, CLU, and APOE genes are associated with episodic memory.Neurology · 2012Article
- William Allan Award Address: On the role and soul of a statistical geneticist.American journal of human genetics · 2011Article
- Pilot study on schizophrenia in Sardinia.Human heredity · 2010Article
- Genome-wide conditional search for epistatic disease-predisposing variants in human association studies.Human heredity · 2010Article
- Prioritizing GWAS results: A review of statistical methods and recommendations for their application.American journal of human genetics · 2010Review
- Detecting gene-gene interactions that underlie human diseases.Nature reviews. Genetics · 2009Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundIn addition to single-locus (main) effects of disease variants, there is a growing consensus that gene-gene and gene-environment interactions may play important roles in disease etiology. However, for the very large numbers of genetic markers currently in use, it has proven difficult to develop suitable and efficient approaches for detecting effects other than main effects due to single variants.
resultsWe developed a method for jointly detecting disease-causing single-locus effects and gene-gene interactions. Our method is based on finding differences of genotype pattern frequencies between case and control individuals. Those single-nucleotide polymorphism markers with largest single-locus association test statistics are included in a pattern. For a logistic regression model comprising three disease variants exerting main and epistatic interaction effects, we demonstrate that our method is vastly superior to the traditional approach of looking for single-locus effects. In addition, our method is suitable for estimating the number of disease variants in a dataset. We successfully apply our approach to data on Parkinson Disease and heroin addiction.
conclusionOur approach is suitable and powerful for detecting disease susceptibility variants with potentially small main effects and strong interaction effects. It can be applied to large numbers of genetic markers.
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