Automated comparison of flow data from HIV and vaccine infected subjects.

描述(申请人提供)：我们实验室构思和开发了最初的流式细胞仪，并自那以后引入了许多创新，增加了这项技术的广泛实用性和可及性。作为这项工作的一部分，我们开发了关键的软件和分析功能，这些功能现在Flow技术的研究和临床用户中无处不在，其中艾滋病毒研究人员和临床医生显然占主导地位。在这里的研究中，我们建议利用我们长期的流动专业知识来引入急需的流动能力，以促进高正常和高通量的工作，以促进艾滋病毒试验样本和疫苗开发过程中分析的样本。基本上，我们建议开发创新方法来自动化流动数据的数据处理和处理任务。这将包括我们最近发表的用于定位和识别感兴趣子集中的细胞的方法的应用，以便我们可以对这些子集中/上的子集标记表达进行统计上的稳健比较。这些方法还将使我们能够开发创新的方法，以识别由试验和/或其他受试者的冷冻或新收集的样本的抗原或其他刺激刺激引起的个别或组标志物变化。重要的是，该软件的目的是(首次)提供一种可靠的单一测量方法，用于在疫苗开发模型中对体内或体外刺激的T细胞亚群诱导的几种细胞内细胞因子表达的非协调变化进行测量。由于它的设计，我们建议以一种易于自动化的集成格式创建我们为这些任务构建的软件，以实现高通量分析。 与公共健康相关：我们建议开发创新的方法来自动化关键处理和数据处理任务，这些任务是直接和自动分析从艾滋病毒研究和疫苗试验的样本中收集的流式细胞仪数据所需的。一旦建立，该软件也将用于艾滋病毒的临床实践。重要的是，我们提出的工作将引入全新的基于统计学的方法来识别T细胞亚群，并应用全新的统计学方法来比较疫苗试验和其他艾滋病毒研究样本刺激引起的亚群标志物表达的变化。与目前所有的方法不同，这些新方法将允许计算对刺激的单一反应指数，即使被测量的反应需要整合T细胞亚群中或其上的几个标记发生的非协调变化的数据。

DESCRIPTION (provided by applicant): Our laboratory conceived and developed the initial flow cytometry instruments and has since introduced many innovations that increase the broad utility and accessibility of this technology. As part of this effort, we developed key software an analysis capabilities that are now ubiquitous among research and clinical users of flow technology, among whom HIV researchers and clinicians clearly predominate. In studies here, we propose to exploit our long-term flow expertise in the interests of introducing much needed flow capabilities to facilitate high normal and high-throughput work HIV trial samples and samples analyzed during vaccine development Basically, we propose to develop innovative methods to automate data handling and processing tasks for flow data. This will include the application of our recently published methods for locating and identifying cells in subsets of interest, so that we can do statistically robust comparisons of subset marker expression in/on these subsets. These methods will also allow us to develop innovative methods for identifying individual or groups of marker changes stimulated by antigen or other stimulation of frozen or freshly collected samples from trial and/or other subjects. Importantly, this software is intended to provide (for the first time) a robust single measure of non-coordinated changes in expression of several intracellular cytokines induced in T cell subsets stimulated in vivo or ex vivo in vaccine development models. Because of its design, we propose to create the software we build for these tasks in an integrated format that is readily amenable to automation to enable high-throughput analyses. PUBLIC HEALTH RELEVANCE: We propose to develop innovative methods to automate key handling and data processing tasks needed for direct and automated analysis of flow cytometry data collected for samples from HIV studies and vaccine trial. Once established, this software will also be useful for HIV clinical practice. Importantly, the work we propose will introduce entirely new statistics-based methods for identification of T cell subsets and the application of entirely new statistical methods to compare changes in subset marker expression induced by stimulation of samples from vaccine trials and other HIV studies. Unlike all current methods, these new methods will allow computation of a single index of response to stimulation, even when the response being measured requires integration of data uncoordinated changes that occur for several markers in or on T cell subsets.