Data Science for Diverse Scholars in Down Syndrome Research (DS3)

唐氏综合症研究中不同学者的数据科学 (DS3)

• 批准号: 10782796
• 负责人: Jack DiGiovanna
• 金额: $ 39.2万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-26 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10782796
• 关键词: Acceleration; Administrative Supplement; Advocate; Award; Bioinformatics; Biometry; Career Mobility; Case Study; Clinical; Cohort Studies; Collection; Colorado; Communities; Data; Data Analyses; Data Coordinating Center; Data Science; Data Set; Development; Dimensions; Discipline; Down Syndrome; Educational Curriculum; Educational process of instructing; Educational workshop; Environment; Event; FAIR principles; Faculty; Feedback; Funding; Future; General Population; Generations; High Performance Computing; Human; Individual; Learning; Life; Linux; Metadata; Minority; Mission; Persons; Postdoctoral Fellow; Proteomics; Pythons; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Resources; Students; Training; Training Programs; Underrepresented Minority; United States National Institutes of Health; Universities; Visualization; Writing; analytical tool; big data management; cloud based; cluster computing; data hub; data portal; data visualization; empowerment; equity, diversity, and inclusion; graduate student; literacy; metabolomics; multidimensional data; multidisciplinary; next generation sequencing; outreach; public repository; responsible research conduct; skills; student training; teacher community; tool; transcriptome; transcriptome sequencing; tutoring

PROJECT SUMMARY. The mission of the INCLUDE Data Coordinating Center (INCLUDE DCC) is to accelerate research that benefits individuals with Down syndrome (DS) by facilitating access and analysis of data from cohort studies of people with DS. A key aspect of this mission is to ensure that the INCLUDE Data Hub and Portal and the datasets hosted in this resource are available to a diverse community of researchers. Therefore, to increase diversity, equity, and inclusion in the INCLUDE Project specifically and in the DS research community more broadly, we propose to develop a training program in data sciences for historically under-represented minorities (URMs). Supported by this administrative supplement, we will complete the second edition of an immersive summer course in data sciences known as the Data Science for Diverse Scholars in Down Syndrome Research (DS3). This course will provide training in the basics of generation, identification, and collection of high content multidimensional datasets; their management, analysis, and visualization, included cloud-based analytics; as well as development of key professional skills required for the career advancement of diverse trainees. Led by a multidisciplinary teaching team, the DS3 will be developed along the following Specific Aims: Aim 1. To teach students how to perform FAIR research in the INCLUDE Data Hub and beyond. We will teach on the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) and demonstrate the FAIR use of datasets available in the INCLUDE Data Hub and other synergistic public repositories. We will tutor students about where to find datasets, how to frame answerable questions, considerations in using public data, and how to analyze these datasets in a cloud-based environment. Aim 2. To train students in the skills necessary for big data management, analysis, and visualization. Using short-read next-generation sequencing data as a foundational data type, students will learn the basics of high-performance computing skills in real life scenarios. Students will be trained on the integration of -omics data types with clinical metadata, data visualization, and diverse biostatistical tools. Aim 3. To empower diverse trainees with professional skills necessary for career advancement. We will teach on the importance of networking, grantsmanship, and presentation skills. Furthermore, we will hold networking events for these students in which they will meet prominent DS researchers and self-advocates invited as guest speakers. Students will also present on their research projects and practice appropriate scientific discourse in providing and receiving feedback. Altogether, this training program will enhance diversity, equity, and inclusion in the pool of young DS researchers, while also elevating data science literacy to accelerate research that will benefit people with DS.

项目总结。 Include数据协调中心(Include DCC)的使命是加速研究 通过促进访问和分析来自人群队列研究的数据，为唐氏综合症(DS)患者提供便利 使用DS。这项任务的一个关键方面是确保包括数据中心和门户以及数据集 在该资源中托管的数据可供不同的研究人员社区使用。因此，为了增加多样性， 公平，并纳入具体的包括项目和更广泛的DS研究社区，我们 提议为历史上代表性不足的少数群体(URM)制定数据科学培训方案。 在这份行政副刊的支持下，我们将完成沉浸式夏季的第二版 数据科学课程，被称为唐氏综合症研究中不同学者的数据科学(DS3)。 本课程将提供生成、识别和收集高内容的基础知识 多维数据集；其管理、分析和可视化，包括基于云的分析；AS 以及发展不同受训人员职业发展所需的关键专业技能。 在一个多学科教学团队的领导下，将按照以下具体目标开发DS3： 目标1.教学生如何在Include Data Hub和其他地方进行公平的研究。我们会 讲授公平原则(可查找性、可访问性、互操作性和可重用性)，并演示 合理使用Include Data Hub和其他协同公共存储库中提供的数据集。我们会做家教 学生了解在哪里找到数据集，如何构建可回答的问题，使用公共数据时的考虑因素， 以及如何在基于云的环境中分析这些数据集。 目标2.培训学生大数据管理、分析和可视化所需的技能。 使用短读下一代测序数据作为基本数据类型，学生将学习基础知识 高性能计算技能在现实生活中的应用。学生将接受关于整合组学的培训 具有临床元数据、数据可视化和各种生物统计工具的数据类型。 目标3.使不同的受训人员掌握职业发展所需的专业技能。我们会 讲授网络、勇气和演讲技巧的重要性。此外，我们将坚持 为这些学生举办的社交活动，在这些活动中，他们将会见著名的DS研究人员和自我倡导者 作为特邀演讲者应邀出席。学生还将介绍他们的研究项目，并实践适当的科学 在提供和接受反馈方面的话语。 总之，这一培训计划将增强多样性、公平性和在年轻DS池中的包容性 研究人员，同时也提高数据科学素养，以加快研究，使DS患者受益。