The Statistical and Computational Analysis of Flow Cytometry Data

流式细胞术数据的统计和计算分析

• 批准号: 8843426
• 负责人: Raphael Gottardo
• 金额: $ 36.08万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-05-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8843426
• 关键词: Address; Algorithms; Basic Science; Biological; Biological Markers; CD4 Positive T Lymphocytes; Cancer Vaccine Related Development; Cell Count; Cells; Cellular biology; Characteristics; Chronic; Classification; Clinical; Clinical Trials; Communities; Computer Analysis; Computing Methodologies; Cytometry; Data; Data Analyses; Data Set; Detection; Diagnosis; Diagnostic; Dimensions; Disease; Disease Outcome; Ensure; Event; Flow Cytometry; Fluorescence; Genetic; Gold; HIV; HIV vaccine; Homeostasis; Immune; Individual; Inflammatory; Informatics; Knowledge; Label; Location; Malaria; Malaria Vaccines; Manuals; Mass Spectrum Analysis; Measurement; Measures; Meta-Analysis; Methodology; Methods; Monitor; Nature; Ontology; Outcome; Play; Population; Process; Research Personnel; Role; Sampling; Software Tools; Solutions; Statistical Methods; Techniques; Technology; Testing; Time; Training; Variant; analytical tool; base; cancer diagnosis; cell type; computerized tools; density; human disease; improved; insight; instrument; interest; next generation; novel; patient oriented; population based; research study; sound; statistics; tool

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.

描述（申请人提供）：流式细胞术是一种数据丰富的技术，在多种人类疾病的基础研究和临床诊断中发挥着关键作用。传统上，大多数细胞计数实验都是通过视觉分析，要么通过一次一维或二维（标记）的连续检查（称为“门控”的过程，用边界或“门”定义感兴趣的细胞群），要么通过汇总统计数据的非常基本的比较。基于原子质谱法的细胞计数技术的进步很快将允许研究人员查询多达 50 个标记（当前技术只能查询约 10 个标记），这使得传统的分析方法变得站不住脚。这种新的质谱流式技术将生成高通量高维数据集，为单细胞生物学开辟新途径。因此，分析工具和统计方法参与这场革命以充分发挥该技术的潜力至关重要。我们正在为流式细胞术和质谱细胞术提出新颖的计算方法和软件工具。这些工具的影响将为研究人员提供一套工具，这些工具对于从此类数据中提取有意义的信息至关重要。我们将把我们的方法应用于许多不同的场景，例如识别艾滋病毒和疟疾疫苗保护的免疫相关性、识别体内平衡的遗传机制以及慢性炎症状况的临床预测。

项目成果

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

• DOI: 10.1007/s11222-010-9204-1
• 发表时间: 2012-01-01
• 期刊: Statistics and computing
• 影响因子: 2.2
• 作者: Lo K;Gottardo R
• 通讯作者: Gottardo R

Merging mixture components for cell population identification in flow cytometry.

• DOI: 10.1155/2009/247646
• 发表时间: 2009
• 期刊: Advances in bioinformatics
• 作者: Finak G;Bashashati A;Brinkman R;Gottardo R
• 通讯作者: Gottardo R

ICEFormat-the image cytometry experiment format.

ICEFormat-图像细胞计数实验格式。

• DOI: 10.1002/cyto.a.22212
• 发表时间: 2012
• 期刊: Cytometry. Part A : the journal of the International Society for Analytical Cytology
• 作者: Spidlen,Josef;Novo,David
• 通讯作者: Novo,David

Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium.

• DOI: 10.1038/srep20686
• 发表时间: 2016-02-10
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: Finak G;Langweiler M;Jaimes M;Malek M;Taghiyar J;Korin Y;Raddassi K;Devine L;Obermoser G;Pekalski ML;Pontikos N;Diaz A;Heck S;Villanova F;Terrazzini N;Kern F;Qian Y;Stanton R;Wang K;Brandes A;Ramey J;Aghaeepour N;Mosmann T;Scheuermann RH;Reed E;Palucka K;Pascual V;Blomberg BB;Nestle F;Nussenblatt RB;Brinkman RR;Gottardo R;Maecker H;McCoy JP
• 通讯作者: McCoy JP

Flow cytometry bioinformatics.

• DOI: 10.1371/journal.pcbi.1003365
• 发表时间: 2013
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: O'Neill K;Aghaeepour N;Spidlen J;Brinkman R
• 通讯作者: Brinkman R