Core 1: Biostatistics and Bioinformatics Core

核心1：生物统计学和生物信息学核心

• 批准号: 10711639
• 负责人: Esther Lu
• 金额: $ 15.04万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-23 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10711639
• 关键词: Adverse event; Bioinformatics; Biological Markers; Biometry; Cancer Center; Clinical Research; Clinical Trials; Collaborations; Computer Analysis; Consult; Core Facility; Data; Data Analyses; Data Collection; Databases; Development; Endometrial Carcinoma; Ensure; Faculty; Genomics; Health Sciences; Immunotherapy; Minority; Monitor; New Mexico; Oklahoma; Output; Quality Control; Reporting; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Resources; Route; Statistical Methods; System; Tissue Sample; Training; Universities; Visualization; Washington; Work; career; data integration; data management; data sharing; design; experience; genomic data; medical schools; meetings; member; next generation sequencing; personalized medicine; programs; targeted therapy trials; trial design

PROJECT SUMMARY The Biostatistics and Bioinformatics Core facility provides state-of-the-art statistical support for all Route 66 Endometrial Cancer SPORE investigators and projects. The Core will provide statistical support on all aspects of study design, study execution and monitoring, database development and quality control, and data analysis and interpretation. Biostatistics and Bioinformatics Core members have diverse expertise, a combined 57 years as faculty biostatisticians and bioinformaticians, and established long-term collaborations with SPORE members at Washington University School of Medicine, University of Oklahoma Health Sciences Center, and University of New Mexico. Their statistical expertise will support newly developing research themes of the SPORE projects, such as Bayesian adaptive trial design, immunotherapy and target therapy trial design, biomarker-guided personalized medicine study, next-generation sequencing, and high-throughput omics data analysis. The Biostatistics and Bioinformatics Core team also has extensive expertise collaborating across centers and in monitoring minority accrual, OnCore, REDCap, and data management/analysis for clinical studies. In Aim 1, the Core will provide biostatistics and bioinformatics collaborations for SPORE projects and Developmental Research Program studies. Core members have and will continue to regularly participate in SPORE project investigator meetings and provide statistical support for designing studies and analyzing data. Additionally, they will help Developmental Research Program awardees design studies and analyze data. In Aim 2, the Core will provide biostatistics and bioinformatics support and training to early-career investigators through the Career Enhancement Program. In their activities, the Core will draw on Clinical Trials Offices in their respective Cancer Centers for multiple purposes: creating forms for data collection, uniform adverse event reports, and tissue sample storage and management; and collating/integrating outputs from high-throughput genomics to streamline data analysis and interpretation. In achieving its aims, the Biostatistics and Bioinformatics Core will ensure that robust statistical methods and reproducible omics analyses are available to support all Route 66 Endometrial Cancer SPORE investigators.

项目摘要 生物统计学和生物信息学核心设施为所有66号公路提供最先进的统计支持 子宫内膜癌孢子研究人员和项目。核心小组将提供各方面的统计支助 研究设计、研究执行和监查、数据库开发和质量控制以及数据分析 和解释。生物统计学和生物信息学核心成员拥有不同的专业知识， 作为生物统计学家和生物信息学家，并与SPORE建立了长期合作关系 华盛顿大学医学院、俄克拉荷马州大学健康科学中心的成员，以及 新墨西哥州大学。他们的统计专业知识将支持新开发的研究主题， SPORE项目，如贝叶斯适应性试验设计、免疫治疗和靶向治疗试验设计， 生物标志物指导的个性化医学研究、下一代测序和高通量组学数据 分析.生物统计学和生物信息学核心团队还拥有广泛的专业知识， 临床试验机构和监测少数应计项目、OnCore、REDCap和数据管理/分析， 问题研究在目标1中，核心将为SPORE项目提供生物统计学和生物信息学合作， 发展研究计划研究。核心成员已经并将继续定期参加 SPORE项目研究者会议，并为设计研究和分析数据提供统计支持。 此外，他们将帮助发展研究计划获奖者设计研究和分析数据。在 目标2，核心将为早期职业研究人员提供生物统计学和生物信息学支持和培训 通过职业提升计划。在他们的活动中，核心将利用临床试验办公室， 他们各自的癌症中心用于多种目的：创建数据收集表格，统一不良事件 报告、组织样本存储和管理;以及整理/整合高通量 基因组学，以简化数据分析和解释。为了实现其目标，生物统计和 生物信息学核心将确保可靠的统计方法和可重复的组学分析可用 支持所有66号公路子宫内膜癌孢子研究者。