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Reconstructability Analysis Of Epistasis, Martin Zwick
Reconstructability Analysis Of Epistasis, Martin Zwick
Systems Science Faculty Publications and Presentations
The literature on epistasis describes various methods to detect epistatic interactions and to classify different types of epistasis. Reconstructability analysis (RA) has recently been used to detect epistasis in genomic data. This paper shows that RA offers a classification of types of epistasis at three levels of resolution (variable-based models without loops, variable-based models with loops, state-based models). These types can be defined by the simplest RA structures that model the data without information loss; a more detailed classification can be defined by the information content of multiple candidate structures. The RA classification can be augmented with structures from related …
Reconstructability Analysis As A Tool For Identifying Gene-Gene Interactions In Studies Of Human Diseases, Stephen Shervais, Patricia L. Kramer, Shawn K. Westaway, Nancy J. Cox, Martin Zwick
Reconstructability Analysis As A Tool For Identifying Gene-Gene Interactions In Studies Of Human Diseases, Stephen Shervais, Patricia L. Kramer, Shawn K. Westaway, Nancy J. Cox, Martin Zwick
Systems Science Faculty Publications and Presentations
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 …