Genetic Analysis of Common Diseases: An Evaluation

摘要 该项目的目标是促进发展和评价统计方法， 描述遗传因素对复杂疾病及其前兆和风险因素的影响。我们提出 为了实现这一目标，继续组织遗传分析讲习班（GAWS），该讲习班始于2004年， 1982.遗传分析研讨会是遗传流行病学家和统计学家之间的合作努力。 遗传学家评估和比较遗传分析方法。对于每一个全球大气观察， 与当前遗传流行病学分析问题的相关性，以及真实的和计算机模拟数据集 分发给世界各地的研究人员。参与者提交他们的分析结果， 并在一个为期三天半的会议上进行了比较。参加全球妇女工作会议的人数大大增加，从不到30人 1982年GAW 1的272至GAW 17的272。在本补助期内，举行了GAW 16（2008年）和GAW 17（2010年）。 GAW 17会议记录目前正在印刷中，预计将于2011年12月出版，并计划于2012年12月出版。 GAW 18开始了。在拟议的赠款期间，GAW 18会议记录将出版， 将举行GAW：GAW 19（2014年）和GAW 20（2017年）。 在研讨会之前，参与者花了几个月的时间进行数据分析， 类似类型的分析，并计划综合介绍。全球大气观察提交的资料总是包含新的 处理复杂表型的方法和许多广泛使用的分析技术的想法已经得到了他们的认可。 从一个GAW开始。最近的GAW包括全基因组关联数据和外显子组序列数据， 参与者有机会尝试定位和表征影响疾病的变异的新方法 风险未来全球大气状况评估的主题将从目前具有挑战性的分析问题中选出。 GAW参与者的建议包括分析全基因组序列的方法;全基因组 甲基化谱;下一代测序项目研究设计的比较;分析 混合群体中的序列数据;基因-环境和基因-基因相互作用;以及拷贝数 变化量 我们还将继续分发真实的和模拟数据从过去的全球大气观测数据的许可 提供商在每次GAW结束很久之后，调查人员继续使用GAW数据集来评估新的 分析方法和软件，以估计功效和假阳性率，并证明可行性 发现疾病基因的统计技术。GAW数据广泛用于赠款提案和 教学和论文研究。

ABSTRACT The goal of this project is to facilitate the development and evaluation of statistical methods for identifying and characterizing the genetic contribution to complex diseases and their precursors and risk factors. We propose to pursue this goal by continuing the organization of the Genetic Analysis Workshops (GAWs), which began in 1982. The Genetic Analysis Workshops are a collaborative effort among genetic epidemiologists and statistical geneticists to evaluate and compare genetic analysis methods. For each GAW, topics are chosen for their relevance to current analytical issues in genetic epidemiology, and sets of real and computer-simulated data are distributed to investigators worldwide. Participants submit the results of their analyses, which are discussed and compared at a 3 1/2 day meeting. Participation at GAWs has increased tremendously, from fewer than 30 at GAW1 in 1982 to 272 at GAW17. In the current grant period GAW16 (2008) and GAW17 (2010) were held. The GAW17 proceedings are currently in press with publication anticipated in December 2011 and planning for GAW18 has begun. During the proposed grant period, the GAW18 Proceedings will be published and two GAWs will be held: GAW19 (in 2014) and GAW20 (in 2017). Before the Workshops, participants devote months to data analysis, communicate with others who have done similar types of analyses, and plan integrated presentations. The GAW submissions invariably contain new ideas for methods to handle complex phenotypes and a number of widely used analytical techniques had their start at a GAW. Recent GAWs have included genome-wide association data and exome sequence data, giving participants an opportunity to try out new methods for localizing and characterizing variants influencing disease risk. Topics for future GAWs will be selected from among currently challenging analytical problems. Suggestions from GAW participants include methods for analyzing whole genome sequence; genome-wide methylation profiles; comparisons of study designs for next generation sequencing projects; analyzing sequence data in admixed populations; gene-environment and gene-gene interactions; and copy number variation. We also will continue to distribute real and simulated data from past GAWs with the permission of the data providers. Long after each GAW is over, investigators continue to use GAW data sets to evaluate new analytical methods and software, to estimate power and false positive rates, and to demonstrate the feasibility of statistical techniques for finding disease genes. GAW data are extensively used in grant proposals and in teaching and dissertation research.