Advances in Statistical Methods for Cancer Genetic Epidemiology

癌症遗传流行病学统计方法的进展

• 批准号: 8459260
• 负责人: JAYA M SATAGOPAN
• 金额: $ 2.25万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2013-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8459260
• 关键词: Address; Area; Breslow Thickness; Cancer Etiology; Case-Control Studies; Classification; Clonality; Cohort Studies; Collaborations; Communication; Communities; Computing Methodologies; Coupled; Data; Detection; Development; Discrimination; Educational workshop; Environmental Carcinogens; Environmental Risk Factor; Epidemiologic Studies; Evaluation; Evaluation of Cancer Risk Factors; Family; Fostering; Future; Genes; Genetic; Genome; Genomics; Goals; Heterogeneity; Investigation; Journals; Malignant Neoplasms; Methodology; Methods; Minority; Molecular Epidemiology; Paper; Pathway interactions; Play; Postdoctoral Fellow; Publishing; Research Design; Research Personnel; Risk Factors; Role; Somatic Mutation; Statistical Methods; Technology; The Cancer Genome Atlas; Underrepresented Minority; Validation; Woman; anticancer research; base; cancer genetics; cancer risk; carcinogenesis; database of Genotypes and Phenotypes; gene environment interaction; genetic epidemiology; genetic variant; genome sequencing; genome wide association study; genome-wide; graduate student; improved; innovation; named group; novel; programs; public health relevance; research study; symposium; trait; tumor; tumor progression; user friendly software

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.

描述（由申请人提供）：基因组学技术的最新进展，加上对推定环境致癌物的研究不断增加，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，在评估和鉴定各种癌症和癌症相关性状的遗传和环境因素方面取得了革命性进展。统计方法在这些研究的有效设计和对所得数据的成功分析中起着关键作用。几 基于快速发展的基因组学技术，已经开发了新的统计方法来满足癌症研究的关键需求。这些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，多种数据类型的整合和纳入途径信息以改善癌症风险因素的检测，罕见遗传变异的评估以及估计癌症绝对风险的改进方法。全基因组体细胞突变数据的可用性和对基因组进行测序以获得关于罕见遗传变异的信息的能力刺激了对诸如癌症的克隆性和癌症亚型的病因异质性等新假设的研究。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。本次研讨会的具体目的是：（1）促进统计和计算方法领域的领先和新兴专家之间的讨论和合作，重点是癌症研究的分子流行病学，以加速新的统计和计算方法的开发和使用;（2）促进一个论坛，让大家就评估各种研究设计所得的数据，交流意见和专门知识;（3）鼓励开发方便使用的软件包;（4）促进使用公开数据来评估这些统计和计算方法;（5）在《遗传流行病学》杂志上发表本次研讨会的精选论文。这是一个开放的研讨会，强调多样性，将作出广泛的努力，包括妇女，代表性不足的少数民族和初级研究人员的计划。