Literature DB >> 23468157

ViSEN: methodology and software for visualization of statistical epistasis networks.

Ting Hu1, Yuanzhu Chen, Jeff W Kiralis, Jason H Moore.   

Abstract

The nonlinear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/.
© 2013 Wiley Periodicals, Inc.

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Year:  2013        PMID: 23468157      PMCID: PMC3758133          DOI: 10.1002/gepi.21718

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


  9 in total

1.  Entropy-based information gain approaches to detect and to characterize gene-gene and gene-environment interactions/correlations of complex diseases.

Authors:  R Fan; M Zhong; S Wang; Y Zhang; A Andrew; M Karagas; H Chen; C I Amos; M Xiong; J H Moore
Journal:  Genet Epidemiol       Date:  2011-11       Impact factor: 2.135

2.  A global view of epistasis.

Authors:  Jason H Moore
Journal:  Nat Genet       Date:  2005-01       Impact factor: 38.330

Review 3.  Genome-wide association studies for common diseases and complex traits.

Authors:  Joel N Hirschhorn; Mark J Daly
Journal:  Nat Rev Genet       Date:  2005-02       Impact factor: 53.242

4.  A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

Authors:  Jason H Moore; Joshua C Gilbert; Chia-Ti Tsai; Fu-Tien Chiang; Todd Holden; Nate Barney; Bill C White
Journal:  J Theor Biol       Date:  2006-02-02       Impact factor: 2.691

5.  The interaction index, a novel information-theoretic metric for prioritizing interacting genetic variations and environmental factors.

Authors:  Pritam Chanda; Lara Sucheston; Aidong Zhang; Murali Ramanathan
Journal:  Eur J Hum Genet       Date:  2009-03-18       Impact factor: 4.246

Review 6.  Detecting gene-gene interactions that underlie human diseases.

Authors:  Heather J Cordell
Journal:  Nat Rev Genet       Date:  2009-06       Impact factor: 53.242

7.  Characterizing genetic interactions in human disease association studies using statistical epistasis networks.

Authors:  Ting Hu; Nicholas A Sinnott-Armstrong; Jeff W Kiralis; Angeline S Andrew; Margaret R Karagas; Jason H Moore
Journal:  BMC Bioinformatics       Date:  2011-09-12       Impact factor: 3.169

8.  Genomewide association studies and human disease.

Authors:  John Hardy; Andrew Singleton
Journal:  N Engl J Med       Date:  2009-04-15       Impact factor: 91.245

9.  An information-gain approach to detecting three-way epistatic interactions in genetic association studies.

Authors:  Ting Hu; Yuanzhu Chen; Jeff W Kiralis; Ryan L Collins; Christian Wejse; Giorgio Sirugo; Scott M Williams; Jason H Moore
Journal:  J Am Med Inform Assoc       Date:  2013-02-08       Impact factor: 4.497

  9 in total
  18 in total

Review 1.  Transdisciplinary approaches enhance the production of translational knowledge.

Authors:  Timothy H Ciesielski; Melinda C Aldrich; Carmen J Marsit; Robert A Hiatt; Scott M Williams
Journal:  Transl Res       Date:  2016-11-10       Impact factor: 7.012

2.  Native American Ancestry and Air Pollution Interact to Impact Bronchodilator Response in Puerto Rican Children with Asthma.

Authors:  María G Contreras; Kevin Keys; Joaquin Magaña; Pagé C Goddard; Oona Risse-Adams; Andrew M Zeiger; Angel C Y Mak; Lesly-Anne Samedy-Bates; Andreas M Neophytou; Eunice Lee; Neeta Thakur; Jennifer R Elhawary; Donglei Hu; Scott Huntsman; Celeste Eng; Ting Hu; Esteban G Burchard; Marquitta J White
Journal:  Ethn Dis       Date:  2021-01-21       Impact factor: 1.847

3.  Genome-wide genetic interaction analysis of glaucoma using expert knowledge derived from human phenotype networks.

Authors:  Ting Hu; Christian Darabos; Maria E Cricco; Emily Kong; Jason H Moore
Journal:  Pac Symp Biocomput       Date:  2015

4.  Heuristic identification of biological architectures for simulating complex hierarchical genetic interactions.

Authors:  Jason H Moore; Ryan Amos; Jeff Kiralis; Peter C Andrews
Journal:  Genet Epidemiol       Date:  2014-11-13       Impact factor: 2.135

5.  Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity.

Authors:  Rishika De; Ting Hu; Jason H Moore; Diane Gilbert-Diamond
Journal:  BioData Min       Date:  2015-12-29       Impact factor: 2.522

6.  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

7.  Epiregulin (EREG) and human V-ATPase (TCIRG1): genetic variation, ethnicity and pulmonary tuberculosis susceptibility in Guinea-Bissau and The Gambia.

Authors:  M J White; A Tacconelli; J S Chen; C Wejse; P C Hill; V F Gomes; D R Velez-Edwards; L J Østergaard; T Hu; J H Moore; G Novelli; W K Scott; S M Williams; G Sirugo
Journal:  Genes Immun       Date:  2014-06-05       Impact factor: 2.676

8.  Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.

Authors:  Ting Hu; Qinxin Pan; Angeline S Andrew; Jillian M Langer; Michael D Cole; Craig R Tomlinson; Margaret R Karagas; Jason H Moore
Journal:  BioData Min       Date:  2014-04-11       Impact factor: 2.522

9.  Computational genetics analysis of grey matter density in Alzheimer's disease.

Authors:  Amanda L Zieselman; Jonathan M Fisher; Ting Hu; Peter C Andrews; Casey S Greene; Li Shen; Andrew J Saykin; Jason H Moore
Journal:  BioData Min       Date:  2014-08-22       Impact factor: 2.522

10.  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

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