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Genetic simulation tools for post-genome wide association studies of complex diseases.

Authors :
Chen HS
Hutter CM
Mechanic LE
Amos CI
Bafna V
Hauser ER
Hernandez RD
Li C
Liberles DA
McAllister K
Moore JH
Paltoo DN
Papanicolaou GJ
Peng B
Ritchie MD
Rosenfeld G
Witte JS
Gillanders EM
Feuer EJ
Source :
Genetic epidemiology [Genet Epidemiol] 2015 Jan; Vol. 39 (1), pp. 11-19. Date of Electronic Publication: 2014 Nov 04.
Publication Year :
2015

Abstract

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.<br /> (© 2014 WILEY PERIODICALS, INC.)

Details

Language :
English
ISSN :
1098-2272
Volume :
39
Issue :
1
Database :
MEDLINE
Journal :
Genetic epidemiology
Publication Type :
Academic Journal
Accession number :
25371374
Full Text :
https://doi.org/10.1002/gepi.21870