ArticleStatistical applications in genetics and molecular biology2010
Reconstructability analysis as a tool for identifying gene-gene interactions in studies of human diseases.
Article in Statistical applications in genetics and molecular biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Construction and analysis of gene-gene dynamics influence networks based on a Boolean model.BMC systems biology · 2017Article
- Evaluating methods for modeling epistasis networks with application to head and neck cancer.Cancer informatics · 2015Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
- TRM: a powerful two-stage machine learning approach for identifying SNP-SNP interactions.Annals of human genetics · 2012Article
- Information metrics in genetic epidemiology.Statistical applications in genetics and molecular biology · 2011Article
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5 authors.
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Abstract
There are a number of common human diseases for which the genetic component may include an epistatic interaction of multiple genes. Detecting these interactions with standard statistical tools is difficult because there may be an interaction effect, but minimal or no main effect. Reconstructability analysis (RA) uses Shannon's information theory to detect relationships between variables in categorical datasets. We applied RA to simulated data for five different models of gene-gene interaction, and find that even with heritability levels as low as 0.008, and with the inclusion of 50 non-associated genes in the dataset, we can identify the interacting gene pairs with an accuracy of > or =80%. We applied RA to a real dataset of type 2 non-insulin-dependent diabetes (NIDDM) cases and controls, and closely approximated the results of more conventional single SNP disease association studies. In addition, we replicated prior evidence for epistatic interactions between SNPs on chromosomes 2 and 15.
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