Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases

被引：13

作者：

Chen, Huann-Sheng ^{[1
]}

Hutter, Carolyn M. ^{[2
]}

Mechanic, Leah E. ^{[3
]}

Amos, Christopher I. ^{[4
]}

Bafna, Vineet ^{[5
]}

Hauser, Elizabeth R. ^{[6
]}

Hernandez, Ryan D. ^{[7
]}

Li, Chun ^{[8
]}

Liberles, David A. ^{[9
]}

McAllister, Kimberly ^{[10
]}

Moore, Jason H. ^{[11
]}

Paltoo, Dina N. ^{[12
]}

Papanicolaou, George J. ^{[13
]}

Peng, Bo ^{[14
]}

Ritchie, Marylyn D. ^{[15
]}

Rosenfeld, Gabriel ^{[1
]}

Witte, John S. ^{[16
]}

Gillanders, Elizabeth M. ^{[3
]}

Feuer, Eric J. ^{[1
]}

机构：

[1] NCI, Surveillance Res Program, Div Canc Control & Populat Sci, NIH, Bethesda, MD 20892 USA

[2] NHGRI, Div Genom Med, NIH, Bethesda, MD 20892 USA

[3] NCI, Epidemiol & Genom Res Program, Div Canc Control & Populat Sci, NIH, Bethesda, MD 20892 USA

[4] Dartmouth Coll, Dept Community & Family Med, Lebanon, NH 03756 USA

[5] Univ Calif San Diego, Dept Comp Sci & Engn, San Diego, CA 92103 USA

[6] Duke Univ, Duke Mol Physiol Inst, Durham, NC USA

[7] Univ Calif San Francisco, Dept Bioengn & Therapeut Sci, San Francisco, CA 94143 USA

[8] Vanderbilt Univ, Dept Biostat, Nashville, TN 37235 USA

[9] Univ Wyoming, Dept Mol Biol, Laramie, WY 82071 USA

[10] NIEHS, Genes Environm & Hlth Branch GEH, NIH, Res Triangle Pk, NC 27709 USA

[11] Dartmouth Coll, Dept Genet, Lebanon, NH 03756 USA

[12] NIH, Off Director, Bethesda, MD 20892 USA

[13] NHLBI, Prevent & Populat Sci Program, Div Cardiovasc Sci, NIH, Bethesda, MD 20892 USA

[14] Univ Texas MD Anderson Canc Ctr, Dept Bioinformat & Computat Biol, Houston, TX 77030 USA

[15] Penn State Univ, Dept Biochem & Mol Biol, University Pk, PA 16802 USA

[16] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA

来源：

GENETIC EPIDEMIOLOGY | 2015年 / 39卷 / 01期

基金：

美国国家科学基金会;

关键词：

genetic simulation; rare variants; next-generation sequencing; complex phenotypes; computational resources; RARE; CANCER; EPIDEMIOLOGY; VARIANTS; MODELS;

D O I：

10.1002/gepi.21870

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

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.

引用

页码：11 / 19

页数：9

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