Large-Scale Statistical Inference: Multiple Testing

大规模统计推断：多重测试

• 批准号: DP150103720
• 负责人: Prof Geoffrey McLachlan
• 金额: $ 19.39万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-01-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP150103720
• 关键词: Large; Scale; Statistical; Inference; Multiple

Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based statistic. They will also exploit contextual information. They are expected to be of direct application to the problem of testing for no differences between two or more classes, as in the detection of differential expression in bioinformatics. Other key applications are expected to include biomedicine, economics, finance, genetics, and neuroscience.

多重检验程序是分析现代数据的最重要的统计工具之一。该项目旨在开发新的方法，以提供更强大的同时测试，同时控制假阳性结论的比例。它们被建议通过在基于单个属性的对比中新的信息汇集来得到，以产生基于加权的单个属性特定对比(WISC)的统计量。他们还将利用上下文信息。它们有望直接应用于测试两个或更多类别之间是否存在差异的问题，如在生物信息学中检测差异表达。预计其他关键应用将包括生物医学、经济、金融、遗传学和神经科学。