Advances in Statistical Methods for Cancer Genetic Epidemiology

描述(申请人提供)：基因组学技术的最新进展，加上对假定的环境致癌物的研究日益增加，通过对候选途径的重点研究以及高通量全基因组关联研究，在评估和识别各种癌症和癌症相关特征的遗传和环境因素方面取得了革命性的进展。统计方法在这些研究的有效设计和对结果数据的成功分析中发挥着关键作用。几个 基于快速发展的基因组学技术，已经开发出新的统计方法来满足癌症研究研究的关键需求。这些措施包括创新的研究设计、研究风险因素之间相互作用的新分析方法、整合多种数据类型和整合路径信息以改进癌症风险因素的检测、评估罕见的基因变异以及改进估计癌症绝对风险的方法。全基因组体细胞突变数据的可获得性以及对基因组测序以获得关于罕见遗传变异的信息的能力刺激了对新假说的研究，如癌症的克隆性和癌症亚型的病因学异质性。因此，为期两天的“癌症遗传流行病学统计方法进展”研讨会将是重要和及时的。这次研讨会的具体目标是：(1)促进统计和计算方法领域的领先专家和新兴专家之间的讨论和合作，以应用于癌症研究，重点是分子流行病学，以加快新的统计和计算方法的开发和使用；(2)促进交流想法和专业知识的论坛，以评估各种研究设计产生的数据；(3)鼓励开发用户友好的软件包；(4)促进使用公开的数据来评估这些统计和计算方法；以及(5)在《遗传流行病学》杂志上发表从这次研讨会中挑选出来的论文。这是一个强调多样性的公开研讨会，将作出广泛努力，将妇女、代表性不足的少数民族和初级研究人员纳入该计划。

DESCRIPTION (provided by applicant): The recent advances in genomics technology, coupled with increasing investigation of putative environmental carcinogens, have led to revolutionary progress in evaluating and identifying genetic and environmental factors for various cancers and cancer-related traits through focused studies of candidate pathways as well as high throughput genome-wide association studies. Statistical methods play a pivotal role in the efficient design of these studies and in the successful analysis of the resulting data. Several novel statistical methods have been developed for addressing the critical needs of cancer research studies based on the rapidly growing genomics technology. These include innovative study designs, novel analytic methods for studying interactions between risk factors, integration of multiple data types and incorporation of pathway information for improving the detection of cancer risk factors, evaluation of rare genetic variants, and improved methods for estimating the absolute risk of cancer. The availability of genome-wide somatic mutation data and the ability to sequence the genome to obtain information on rare genetic variants have stimulated the investigation of novel hypotheses such as clonality of cancer and etiologic heterogeneity of cancer subtypes. Therefore, a two-day symposium on "Advances in Statistical Methods for Cancer Genetic Epidemiology" would be important and timely. The Specific Aims of this symposium are: (1) to promote discussions and collaborations among leading and emerging experts in the area of statistical and computational methods with application to cancer research with emphasis on molecular epidemiology for accelerating the development and use of novel statistical and computational methods; (2) to promote a forum for the interchange of ideas and expertise for evaluating data arising from a variety of study designs; (3) to encourage the development of user-friendly software packages; (4) to promote the use of publicly available data to assess these statistical and computational methods; and (5) to publish select papers from this workshop in the journal Genetic Epidemiology. This is an open symposium with an emphasis on diversity, where extensive efforts will be made to include women, under-represented minority, and junior researchers in the program.