Resolving Methodological Challenges in Genomics Research: Causality, Risk Prediction, and Reproducibility: Administrative Supplement

解决基因组学研究中的方法学挑战：因果关系、风险预测和再现性：行政补充

• 批准号: 10392682
• 负责人: Xiaoquan Wen
• 金额: $ 0.83万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10392682
• 关键词: Administrative Supplement; Biological; Biomedical Research; Communities; Complex; Computer software; Disease; Etiology; Genetic; Genomics; Knowledge; Lead; Medical; Methodology; Molecular; Reproducibility; Research; Scientist; computerized tools; genomic data; improved; large scale data; public health relevance; risk prediction; tool; treatment strategy; user-friendly

Project Summary This proposed project focuses on the statistical assessment of reproducibility in genomic and genetic applications. Reproducibility is a hallmark of scientific research. However, the quantitative tools for evaluating reproducibility and replicability are still lacking. We will develop and apply computational tools to assess reproducibility in findings from genetic and genomic research. We will build user-friendly computational software packages and make them available to the broad community of biological and medical scientists.

项目摘要 这项拟议的项目侧重于对基因组和 基因应用。可重复性是科学研究的一个标志。然而，数量上的 目前仍缺乏评估可再现性和可复制性的工具。我们将开发和应用 评估遗传和基因组研究结果的重复性的计算工具。我们 将构建用户友好的计算软件包，并将其提供给广大用户 生物和医学科学家的社区。