Bioinformatics Resource Core

摘要 随着高维数据的可获得性，临床研究的瓶颈已经从缺乏 从生物数据到缺乏高质量的表型数据。个性化医疗的前景只能是 如果调查人员可以研究集成数据集中数百万受试者的数据，该数据集中包含准确的 表型。在我们实现这一目标之前，存在着几个挑战。首先，需要健壮的方法来 在大量患者中集成不同类型的数据，包括电子病历(EMR) 将数据、患者报告的结果测量和基因分型数据合并到高维数据集中。第二，小说 需要一些方法来准确和有效地识别具有特定感兴趣表型的患者。 解决这些挑战将使我们能够将高维数据集的信息转换为 可以改善病人护理的发现。Verity生物信息学资源核心的总体目标 是支持Verity研究社区应用最先进的生物信息学方法来增强 儿童和成人风湿和肌肉骨骼(MSK)疾病的临床研究。 现在存在强大的生物信息学方法和工具，可以提供基础设施来标准化和 组织复杂的数据。因此，研究人员可以跨以前不同的数据集进行查询以进行分析 并使用新的可视化技术汇总数据，消除了翻译的许多障碍 学习。虽然这些平台最初是为一般人口研究而设计的，但我们将利用这些 风湿病和MSK疾病研究的工具。利用使用高维数据的经验 研究，核心教职员工将为Verity研究社区提供支持和指导 结合这些方法的方法和工具通过 以下具体目标：目标1.建立和定制最先进的生物信息学平台，以支持 风湿病和MSK临床数据共享和协作研究。次级目标包括：建立一个 发布的开源生物信息学平台，标准化和集成各种数据类型，并允许 用户实时可视化和查询数据；并在风湿病和MSK之间建立合作伙伴关系 临床研究和生物信息学社区通过核心咨询服务。目标2.提供和 支持一套可直接应用于临床研究的生物信息学工具。 总之，Verity生物信息学核心将建立一个最先进的生物信息学平台 风湿病和MSK病的临床研究，应用开源代码和数据可视化的原则。 核心将把我们目前的工作扩展到在不同地点工作的研究社区 NIAMS任务驱动的条件范围。此外，Verity提出的研究问题将提出 新的方法学挑战，推动生物信息学方法的进步，培育新的 合作。

ABSTRACT With the availability of high-dimensional data, the bottleneck in clinical research has shifted from a paucity of biologic data to a paucity of high quality phenotypic data. The promise of personalized medicine can only be realized if investigators can study the data of millions of subjects in an integrated dataset containing accurate phenotypes. Several challenges exist before we can realize this goal. First, robust methods are needed to integrate different types of data in large populations of patients, including electronic medical record (EMR) data, patient reported outcomes measures, and genotypic data, into high dimensional datasets. Second, novel approaches are needed to accurately and efficiently identify patients with specific phenotypes of interest. Addressing these challenges will allow us to translate the information from high-dimensional datasets to discoveries that can improve patient care. The overarching goal of the VERITY Bioinformatics Resource Core is to support the VERITY Research Community to apply state-of-the art bioinformatics methods to enhance clinical research in pediatric and adult rheumatic and musculoskeletal (MSK) diseases. Powerful bioinformatics methods and tools now exist that can provide the infrastructure to standardize and organize complex data. Consequently, researchers can query across formerly disparate datasets to analyze and summarize data using new visualization techniques, removing many of the barriers for translational studies. While these platforms were initially designed for general population studies, we will harness these tools for rheumatic and MSK disease research. Drawing on experience using high dimensional data for research, the Core faculty and staff will provide support and guidance to the VERITY Research Community on the methods and tools to incorporate these approaches to advance clinical research studies through the following Specific Aims: Aim 1. To establish and customize a state-of-the-art bioinformatics platform to support rheumatic and MSK clinical data for sharing and collaborative research. Sub-aims include: to establish a published, open-source bioinformatics platform that standardizes and integrates diverse data types, and allows users to visualize and query the data in real time; and to forge partnerships between the rheumatic and MSK clinical research and bioinformatics communities through core consulting services. Aim 2. To provide and support a suite of bioinformatics tools with direct applications to clinical research studies. In sum, the VERITY Bioinformatics Core will establish a state-of-the-art bioinformatics platform for rheumatic and MSK disease clinical research, applying principles of open-source code and data visualization. The Core will extend our current work to the Research Community working in different locations on a wide range of NIAMS-mission driven conditions. Moreover, the research questions arising from VERITY will present new methodologic challenges, driving advancement of bioinformatics methods and fostering new collaborations.