Core 2: Bioinformatics and Biostatistics Core

核心2：生物信息学和生物统计学核心

• 批准号: 10251113
• 负责人: Ying Yuan
• 金额: $ 16.38万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-22 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10251113
• 关键词: Address; Aftercare; Automobile Driving; Bioinformatics; Biological Assay; Biometry; Biopsy; Biostatistics Core; Cancer Center; Characteristics; Clinical Data; Clinical Trials; Complex; Coupling; Data; Data Analyses; Data Analytics; Doctor of Medicine; Dose; Epigenetic Process; Evaluation; Experimental Designs; Gene Chips; Goals; Hand; Malignant neoplasm of ovary; Methods; Methylation; Mind; Morphologic artifacts; Mutation Analysis; Operative Surgical Procedures; Outcome; Ovarian; Patients; Phase; Phenotype; Population; Randomized; Research; Research Methodology; Research Personnel; Risk; Running; Sampling; Specific qualifier value; Surveys; The Cancer Genome Atlas; Thinking; Training; clinically relevant; computerized data processing; design; efficacy testing; flexibility; high throughput screening; improved; interest; meetings; member; next generation sequencing; novel therapeutics; predicting response; predictive marker; simulation; statistics; tool

Core 2: Biostatistics and Bioinformatics SUMMARY/ABSTRACT All projects in this Ovarian SPORE generate large amounts of data using a wide variety of assays, and are associated with clinical trials testing the efficacy of new therapeutic options. The Biostatistics and Bioinformatics Core (Core 2) provides the quantitative expertise required to distill useful information from these various types of data, and to design and analyze the data from the clinical trials being run. Neither of these tasks is trivial. Assays now available (e.g., next-generation sequencing for mutation analysis, methylation arrays for epigenetic studies, expression arrays) are extremely powerful and can detect subtle changes that may be driving phenotypic changes, but this very sensitivity means they are also quite capable of detecting assay artifacts if proper experimental design (e.g., randomization) is not used. Further, the raw data generated requires substantial preprocessing before valid inferences can be drawn. Members of Core 2 have the training to address these tasks, which are common to the various projects—many of the same assays are being used with different experimental goals in mind, but the data analytic questions are parallel. Similarly, while all clinical trials have common goals (dose finding, treatment assessment), explicitly specifying what must be done to produce trials likely to provide the most information while putting the fewest patients at risk requires expertise in both the elicitation of relevant information and the ability to examine likely outcomes (often through simulation). Some common designs exist for the most frequent approaches pursued, but recent advances in the past few decades have allowed us to develop new strategies that may be better suited to the tasks at hand where the computing power now exists to explore how the operating characteristics are improved. Providing optimal support for the projects also requires the flexibility to address new challenges and opportunities that may arise. In this iteration of the SPORE, some of these challenges and opportunities include trying to optimally exploit both (a) data uniquely available within MD Anderson, where coupling of laparoscopic examination and biopsies with surgical evaluation lets us acquire both pre- and post-treatment samples from the population of interest, and (b) the wealth of public profiling data (e.g. TCGA ovarian assays) which can help winnow real phenomena from chaff. Core 2 has this flexibility, and is working with SPORE investigators on these tasks even now. Further, as the studies being pursued in the SPORE show, the separation between complex assays and clinical trials is becoming increasingly blurred. Moving forward will require clear thinking about what types of inferences can be reliably used, and how. Members of Core 2 are widely recognized for their contributions to this debate, which enables them to better support the SPORE.

核心2：生物统计和生物信息学摘要/摘要 这个卵巢孢子中的所有项目都使用各种分析方法产生大量数据，并 与测试新治疗方案疗效的临床试验有关。生物统计学和 生物信息学核心(核心2)提供从这些信息中提取有用信息所需的量化专业知识 各种类型的数据，并设计和分析正在进行的临床试验的数据。这两个都不是 任务是琐碎的。现在可以进行分析(例如，用于突变分析、甲基化的下一代测序 用于表观遗传学研究的阵列，表达阵列)非常强大，可以检测到 可能推动了表型变化，但这种敏感性意味着它们也很有能力检测到 如果没有使用适当的实验设计(例如，随机化)，则检测伪影。此外，生成的原始数据 在得出有效的推论之前，需要进行大量的预处理。核心2的成员接受了培训 为了解决这些任务，这些任务对各种项目来说是常见的--正在使用许多相同的分析方法 心中有不同的实验目标，但数据分析问题是平行的。同样，虽然所有的临床 试验有共同的目标(剂量发现、治疗评估)，明确规定必须采取哪些措施 生产可能提供最多信息的试验，同时将最少的患者置于危险之中需要专业知识 在获取相关信息和检查可能结果的能力方面(通常通过 模拟)。对于最常用的方法存在一些常见的设计，但最近在 在过去的几十年里，我们制定了可能更适合手头任务的新战略 这里的计算能力现在存在，以探索如何改善操作特性。 为项目提供最佳支持还需要灵活应对新的挑战和 可能出现的机会。在孢子的这一次迭代中，这些挑战和机遇中的一些 包括试图以最佳方式利用(A)MD Anderson中唯一可用数据，其中耦合 腹腔镜检查和活组织检查结合手术评估使我们能够获得治疗前和治疗后的信息 来自感兴趣人群的样本，以及(B)丰富的公共概况数据(例如TCGA卵巢分析) 这可以帮助从谷壳中筛选出真实的现象。核心2具有这种灵活性，并且正在与孢子一起工作 调查人员至今仍在执行这些任务。 此外，正如孢子中正在进行的研究表明，复杂的分析和 临床试验正变得越来越模糊。前进将需要清楚地思考哪些类型的 推论可以可靠地使用，以及如何使用。核心2的成员因其在以下方面的贡献而广受认可 这场辩论，使他们能够更好地支持孢子。