Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans.

By Heather J. Cordell. Human Molecular Genetics, 2002

1,130 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/30015a3a5f08fc9aefb55973aecad2b33c6c5ba6

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Citations in the corpus

A Tutorial on Interaction (2014, background): “Statistical analyses can only tell us limited information about the underlying biology (Siemiatycki and Thomas, 1981; Thompson, 1991; Rothman and Greenland, 1998; Cordell, 2002).”
A tutorial on statistical methods for population association studies (2006, background): “The study of epistasis poses problems of interpretabilit”
GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures (2012, background): “Computational geneticists are putting significant effort into developing algorithms for the detection of complex disease associations within clinical data [6-9].”
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data (2009, methodology): “In this supplement, we describe the following points in detail: 1) The proposed method, particularly the pseudocode of each part of our method, and 2) Experimental results, particularly the result obtained by using the GEO (Gene Expression Omnibus) database (Barrett et al., 2007) extensively.”
Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection (2012, background): “epistasis) is a significant challenge driving bioinformatic development [1-4].”
SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies (2009, background): “These multiple genetic variations may show very little effect individually but strong interactions jointly, which is known as epistasis or multilocus interaction (Cordell, 2002).”
Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. (2005, methodology): “Cordell((26))) or nonparametric methods such as combinatorial partitioning, restricted partitioning,((30)) set association analysis, genetic programming neural networks((36,37)) and multifactor dimensionality reduction”
BOOST: A fast approach to detecting gene-gene interactions in genome-wide case-control studies (2010, methodology): “Regarding the interaction test, both INTERSNP and our work are developed on the basis of the standardized definition using logistic regression models.(13) INTERSNP has directly used”