Literature DB >> 23934759

EINVis: a visualization tool for analyzing and exploring genetic interactions in large-scale association studies.

Yubao Wu1, Xiaofeng Zhu, Jian Chen, Xiang Zhang.   

Abstract

Epistasis (gene-gene interaction) detection in large-scale genetic association studies has recently drawn extensive research interests as many complex traits are likely caused by the joint effect of multiple genetic factors. The large number of possible interactions poses both statistical and computational challenges. A variety of approaches have been developed to address the analytical challenges in epistatic interaction detection. These methods usually output the identified genetic interactions and store them in flat file formats. It is highly desirable to develop an effective visualization tool to further investigate the detected interactions and unravel hidden interaction patterns. We have developed EINVis, a novel visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. It utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions. It is publicly available with detailed documentation and online tutorial on the web at http://filer.case.edu/yxw407/einvis/.
© 2013 WILEY PERIODICALS, INC.

Entities:  

Keywords:  epistasis; gene-gene interaction; networks; software; visualization

Mesh:

Substances:

Year:  2013        PMID: 23934759      PMCID: PMC6309325          DOI: 10.1002/gepi.21754

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  27 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Hierarchical edge bundles: visualization of adjacency relations in hierarchical data.

Authors:  Danny Holten
Journal:  IEEE Trans Vis Comput Graph       Date:  2006 Sep-Oct       Impact factor: 4.579

Review 3.  Tools for visually exploring biological networks.

Authors:  Matthew Suderman; Michael Hallett
Journal:  Bioinformatics       Date:  2007-08-25       Impact factor: 6.937

4.  SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap.

Authors:  Andrew D Johnson; Robert E Handsaker; Sara L Pulit; Marcia M Nizzari; Christopher J O'Donnell; Paul I W de Bakker
Journal:  Bioinformatics       Date:  2008-10-30       Impact factor: 6.937

5.  CACNA1C polymorphisms are associated with the efficacy of calcium channel blockers in the treatment of hypertension.

Authors:  Troy Bremer; Albert Man; Kalev Kask; Cornelius Diamond
Journal:  Pharmacogenomics       Date:  2006-04       Impact factor: 2.533

Review 6.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

7.  Genetic polymorphisms of L-type calcium channel alpha1C and alpha1D subunit genes are associated with sensitivity to the antihypertensive effects of L-type dihydropyridine calcium-channel blockers.

Authors:  Kei Kamide; Jin Yang; Tetsutaro Matayoshi; Shin Takiuchi; Takeshi Horio; Masayoshi Yoshii; Yoshikazu Miwa; Hisayo Yasuda; Fumiki Yoshihara; Satoko Nakamura; Hajime Nakahama; Toshiyuki Miyata; Yuhei Kawano
Journal:  Circ J       Date:  2009-02-17       Impact factor: 2.993

8.  Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

Authors:  Brendan J Keating; Sam Tischfield; Sarah S Murray; Tushar Bhangale; Thomas S Price; Joseph T Glessner; Luana Galver; Jeffrey C Barrett; Struan F A Grant; Deborah N Farlow; Hareesh R Chandrupatla; Mark Hansen; Saad Ajmal; George J Papanicolaou; Yiran Guo; Mingyao Li; Stephanie Derohannessian; Paul I W de Bakker; Swneke D Bailey; Alexandre Montpetit; Andrew C Edmondson; Kent Taylor; Xiaowu Gai; Susanna S Wang; Myriam Fornage; Tamim Shaikh; Leif Groop; Michael Boehnke; Alistair S Hall; Andrew T Hattersley; Edward Frackelton; Nick Patterson; Charleston W K Chiang; Cecelia E Kim; Richard R Fabsitz; Willem Ouwehand; Alkes L Price; Patricia Munroe; Mark Caulfield; Thomas Drake; Eric Boerwinkle; David Reich; A Stephen Whitehead; Thomas P Cappola; Nilesh J Samani; A Jake Lusis; Eric Schadt; James G Wilson; Wolfgang Koenig; Mark I McCarthy; Sekar Kathiresan; Stacey B Gabriel; Hakon Hakonarson; Sonia S Anand; Muredach Reilly; James C Engert; Deborah A Nickerson; Daniel J Rader; Joel N Hirschhorn; Garret A Fitzgerald
Journal:  PLoS One       Date:  2008-10-31       Impact factor: 3.240

9.  A survey of visualization tools for biological network analysis.

Authors:  Georgios A Pavlopoulos; Anna-Lynn Wegener; Reinhard Schneider
Journal:  BioData Min       Date:  2008-11-28       Impact factor: 2.522

10.  Admixture mapping provides evidence of association of the VNN1 gene with hypertension.

Authors:  Xiaofeng Zhu; Richard S Cooper
Journal:  PLoS One       Date:  2007-11-28       Impact factor: 3.240

View more
  3 in total

1.  An interaction quantitative trait loci tool implicates epistatic functional variants in an apoptosis pathway in smallpox vaccine eQTL data.

Authors:  C A Lareau; B C White; A L Oberg; R B Kennedy; G A Poland; B A McKinney
Journal:  Genes Immun       Date:  2016-04-07       Impact factor: 2.676

2.  Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks.

Authors:  Ting Hu; Angeline S Andrew; Margaret R Karagas; Jason H Moore
Journal:  BioData Min       Date:  2015-12-21       Impact factor: 2.522

3.  CINOEDV: a co-information based method for detecting and visualizing n-order epistatic interactions.

Authors:  Junliang Shang; Yingxia Sun; Jin-Xing Liu; Junfeng Xia; Junying Zhang; Chun-Hou Zheng
Journal:  BMC Bioinformatics       Date:  2016-05-17       Impact factor: 3.169

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.