Paper Info
Title
CINOEDV: A co-information based method for detecting and visualizing n-order epistatic interactions
Abstract
Background: Detecting and visualizing nonlinear interaction effects of single nucleotide polymorphisms (SNPs) or epistatic interactions are important topics in bioinformatics since they play an important role in unraveling the mystery of 'missing heritability'. However, related studies are almost limited to pairwise epistatic interactions due to their methodological and computational challenges. Results: We develop CINOEDV (Co-Information based N-Order Epistasis Detector and Visualizer) for the detection and visualization of epistatic interactions of their orders from 1 to n (n _ 2). CINOEDV is composed of two stages, namely, detecting stage and visualizing stage. In detecting stage, co-information based measures are employed to quantify association effects of n-order SNP combinations to the phenotype, and two types of search strategies are introduced to identify n-order epistatic interactions: an exhaustive search and a particle swarm optimization based search. In visualizing stage, all detected n-order epistatic interactions are used to construct a hypergraph, where a real vertex represents the main effect of a SNP and a virtual vertex denotes the interaction effect of an n-order epistatic interaction. By deeply analyzing the constructed hypergraph, some hidden clues for better understanding the underlying genetic architecture of complex diseases could be revealed. Conclusions: Experiments of CINOEDV and its comparison with existing state-of-the-art methods are performed on both simulation data sets and a real data set of age-related macular degeneration. Results demonstrate that CINOEDV is promising in detecting and visualizing n-order epistatic interactions. CINOEDV is implemented in R and is freely available from R CRAN: http://cran.r-project.organd https://sourceforge.net/projects/cinoedv/files/. © 2016 Shang et al.
Year
DOI
Venue
2016
10.1186/s12859-016-1076-8
BMC Bioinformatics
Keywords
Field
DocType
Co-information,Epistatic interactions,Hypergraph,Particle swarm optimization,Single nucleotide polymorphisms
Pairwise comparison,Genetic architecture,Missing heritability problem,Biology,Brute-force search,Visualization,Epistasis,Hypergraph,Bioinformatics,Computational biology,Genetics,Main effect
Journal
Volume
Issue
ISSN
17
1
1471-2105
Citations 
PageRank 
References 
3
0.42
13
Authors
6
Name
Order
Citations
PageRank
Junliang Shang14214.78
Sun Yingxia230.42
Liu Jin-Xing34016.11
Junfeng Xia4224.04
Junying Zhang5302.70
Chun-Hou Zheng6253.91