Chen Huann-Sheng, Hutter Carolyn M, Mechanic Leah E, Amos Christopher I, Bafna Vineet, Hauser Elizabeth R, Hernandez Ryan D, Li Chun, Liberles David A, McAllister Kimberly, Moore Jason H, Paltoo Dina N, Papanicolaou George J, Peng Bo, Ritchie Marylyn D, Rosenfeld Gabriel, Witte John S, Gillanders Elizabeth M, Feuer Eric J
Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892.
Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD 20892.
Genet Epidemiol. 2015 Jan;39(1):11-19. doi: 10.1002/gepi.21870. Epub 2014 Nov 4.
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.
遗传模拟程序用于在特定假设下对数据进行建模,以促进对复杂遗传系统的理解和研究。使用遗传模拟生成的标准化数据集对于遗传流行病学研究中新型分析工具的开发和应用至关重要。随着高通量基因组技术的不断进步以及更大、更复杂数据集的生成和分析,有必要更新遗传模拟建模的当前方法。为了提供一个论坛来应对该领域当前和新出现的挑战,美国国立癌症研究所(NCI)于2014年3月11日至12日在马里兰州贝塞斯达的国立卫生研究院(NIH)主办了一次题为“复杂疾病基因组全关联研究后的遗传模拟工具”的研讨会。该研讨会的目标是:(1)确定遗传模拟模型开发和应用的机遇、挑战及资源需求;(2)改善模拟数据建模和分析工具的整合;(3)促进合作以推动遗传模拟的开发和应用。在会议过程中,该小组确定了模拟科学、软件和方法开发以及合作方面的挑战和机遇。本文总结了会议的关键讨论内容,并突出了推进遗传模拟领域发展的重要挑战和机遇。