Critical Assessment of Genome Interpretation Conference

描述（由申请人提供）：我们建议在2012年12月和2013年12月再组织两次基因组解释关键评估（CAGI）会议。与2010年和2011年一样，这次会议将是一个社区实验的高潮，目的是客观地评估预测基因组变异的表型影响的计算方法。由于个体基因组的迅速可用性，以及对这些研究和临床应用进行解释的愿望，CAGI实验是及时和广泛相关的。目前，该领域对各种不同预测方法的绝对适用性和相对适用性缺乏共识。这些会议将首次对基因组变异解释技术的现状进行大规模评估。会议的结果将予以公布，以确保广泛传播会议结果。在以结构预测关键评估（CASP）为模型的cai实验中，参与者被提供遗传变异，并对产生的分子、细胞或有机体表型进行预测。预计数据集将包括罕见疾病、常见性状和疾病、种系和体细胞癌症变异，重点关注基因组和外显子组、非单核苷酸多态性、影响剪接的单核苷酸多态性、拷贝数变异以及转录组学等其他数据。独立评估人员将根据实验表征的表型评估预测。每次实验结束时，将举行一次CAGI会议。会议的具体目标是：(1)评估当前用于解释基因组数据的计算方法的质量，并突出创新和进展；(2)指导未来在计算基因组解释方面的研究工作，并建立一个强大的协作和互动社区；(3)在会议上向变异表型预测社区的主要成员传播结果，并通过在同行评审期刊上发表结果向更广泛的受众传播结果。新的CAGI实验将继续从2010年的CAGI试点开始的过程，并在2011年进行第一次全尺寸CAGI实验。2011年的实验在来自18个国家的21个小组的11个数据集上总共产生了117个预测。55人参加了2011年12月的会议，我们正在通过开放获取出版物和会议报告传播结果。参与社区的绝大多数人认为这个实验是必要的，应该在持续的基础上再次组织。组织者将大力鼓励妇女和代表性不足的少数民族，以及学员和资深科学家广泛参与CAGI会议。请拨经费为学生和博士后研究人员提供19个实习研究金，以支付注册费用和大约三分之二的其他会议参加费用（旅费和生活津贴）。此外，我们寻求资金补贴注册和大约一半的会议参与费用的独立评审员，一些数据提供者和科学委员会成员，以及CAGI实验的组织者。

DESCRIPTION (provided by applicant): We propose to organize two further Critical Assessment of Genome Interpretation (CAGI) meetings, in December 2012 and December 2013. As in 2010 and 2011, the meetings will be the culmination of a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. The CAGI experiment is timely and of wide relevance due to the burgeoning availability of individuals' genomes, and the desire to interpret these for research and clinical applications. Currently, the field lacks a consensus on the absolute and relative suitability of th panoply of different methods for prediction. These meetings will provide the first large-scale assessment of the state of the art of genome variation interpretation. The outcome of the meetings will be published to ensure wide dissemination of results. In the CAGI experiments, modeled on the Critical Assessment of Structure Prediction (CASP), participants are provided genetic variants and make predictions of resulting molecular, cellular, or organismal phenotype. Datasets are expected to include rare disease, common traits and diseases, germline and somatic cancer variation, with a focus on genomes and exomes, nsSNPs, splice-affecting SNPs, and copy number variation along with other data such as transcriptomics. Independent assessors will evaluate the predictions against experimentally characterized phenotypes. A CAGI Conference is held at the end of each experiment. The specific goals of the meeting are: (1) to assess the quality of current computational methods for interpreting genomic data, and highlight innovations & progress; (2) to guide future research efforts in computational genome interpretation and build a strong community for collaboration and interaction; and (3) to disseminate results both amongst key members of the variant-phenotype prediction community at the meeting and to a broader audience via publication of results in peer-reviewed journals. The new CAGI experiments will continue the process started with the CAGI pilot in 2010, and the first full-scale CAGI experiment in 2011. The 2011 experiment yielded a total of 117 predictions on 11 datasets, from 21 groups from 18 countries. 55 people attended the December 2011 meeting, and we are disseminating results via open access publications and conference presentations. The participating community was overwhelmingly of the opinion that this experiment is necessary and should be organized again on an ongoing basis. The organizers will strongly encourage the participation of women and underrepresented minorities, and broad participation of trainees and senior scientists at the CAGI meeting. Funding is requested for awarding 19 trainee fellowships for students and postdoctoral researchers to cover registration and approximately 2/3 of their other meeting participation costs (travel and subsistence). In addition, we seek funding to subsidize registration and approximately half of meeting participation costs of the independent assessors, some data providers and scientific council members, and the organizers of the CAGI experiments. PUBLIC HEALTH RELEVANCE: Genomic variation is responsible for numerous rare diseases, propensity for many common traits and diseases, drug response, and is a key characteristic of cancer evolution. At present, our ability to characterize genetic differences far exceeds our capacity to interpret it either for basic research understanding or for clinical diagnosis. The Critical Assessment of Genome Interpretation will provide an evaluation of the current state-of-the-art and help promote progress in understanding genomic variation.