The Statistical and Computational Analysis of Flow Cytometry Data

描述（由申请人提供）：流式细胞术是一项数据丰富的技术，在各种人类疾病的基础研究和临床诊断中起着至关重要的作用。传统上，大多数细胞术实验都是通过视觉分析，或者通过一次对一个或两个维度（标记）的连续检查（这一过程被称为“门控”，用边界或“门”定义感兴趣的细胞群），或者通过非常基本的汇总统计比较。基于原子质谱的细胞测定技术的进步将很快使研究人员能够查询多达50个标记（而当前技术只能查询大约10个），这使得传统的分析方法站不住脚。这种新的细胞计数技术将产生高通量高维数据集，为单细胞生物学开辟了新的途径。因此，分析工具和统计方法必须参与这场革命，以充分利用这项技术的潜力。我们正在为流式细胞术和质量细胞术提出新的计算方法和软件工具。这些工具的影响将是为研究人员提供一套工具，这些工具将成为从这些数据中提取有意义信息的必要工具。我们将把我们的方法应用于许多不同的场景，如鉴定艾滋病毒和疟疾疫苗保护的免疫相关性，鉴定体内平衡的遗传机制，以及慢性炎症条件的临床预测。

DESCRIPTION (provided by applicant): Flow cytometry is a data-rich technology that plays a critical role in basic research and clinical diagnostics for a variety of human diseases. Traditionally, the majority of cytometry experiments have been analyzed visually, either by serial inspection of one or two dimensions (markers) at a time (a process termed "gating", with boundaries or "gates" defining cell populations of interest), or by very basic comparisons of summary statistics. Technological advances in cytometry based on atomic mass spectrometry will soon allow researchers to query up to 50 markers (as opposed to about 10 with current technology), making traditional analysis approaches untenable. This new mass cytometry technology will generate high-throughput high-dimensional datasets, opening up new avenues for single--cell biology. As a consequence, it is essential that analytical tools and statistical methods take part in this revolution to harness the full potential of the technology. We are proposing novel computational methods and software tools for both flow and mass cytometry. The impact of these tools will be to provide researchers with a set of tools that will become essential to extract meaningful information from such data. We will apply our methods to a number of different scenarios such as the identification of immune correlate of protections for HIV and malaria vaccines, the identification of genetic mechanisms of homeostasis, and the clinical prediction of chronic inflammatory conditions.