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

自动比较 HIV 和疫苗感染受试者的流量数据。

• 批准号: 9303874
• 负责人: Leonore A. Herzenberg
• 金额: $ 24.15万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-06 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9303874
• 关键词: Area; Attention; Automation; Biological Markers; CD4 Positive T Lymphocytes; Cell Communication; Cell Count; Cells; Charge; Clinical Research; Computer software; Cytometry; Data; Data Analyses; Data Display; Data Set; Development; Disease; Dyes; Financial compensation; Flow Cytometry; Fluorescence; Funding; Future; HIV; HIV vaccine; Immune system; Institution; Laboratories; Laboratory Study; Measurement; Measures; Methods; Modeling; Outcomes Research; Population; Probability; Research; Research Personnel; Sampling; Software Tools; Speed; Staining method; Stains; System; Systems Development; T-Lymphocyte Subsets; Technology; Vaccines; Visual; Work; base; cytokine; data acquisition; design; drug development; experimental study; high dimensionality; improved; in vivo; indexing; innovation; instrument; instrumentation; pathogen; public health relevance; response; simulation; tool; two-dimensional; user-friendly; vaccine trial

 DESCRIPTION (provided by applicant): Our laboratory is well known for having developed and broadly disseminated flow cytometry technology, starting with development of the first FACS and continuing thereafter to add innovative improvements both to the instrument itself and the software that now replaces and greatly extends the initial capabilities. Our earlier work, for which our laboratory is renowned, includes the shift from hardware to software based fluorescence compensation, the development of the now-ubiquitous "probability" contours for displaying two-dimensional flow data, and the development of "Logicle" (aka "Bi-exponential") display axes that are fast becoming ubiquitous. Continuing in this tradition, we have turned our attention to automating fluorescence compensation and flow data analysis to enable researchers and clinicians at all levels to take full advantage of the capabilities offered by today's High-Dimensional (Hi-D) flow cytometry instruments. Supported by the R01 for which we seek renewal here, this project has already generated a spate of user-friendly automated software "tools" that provide accessible, statistically appropriate methods for processing and analyzing flow data. These include 1) statistically-based automated fluorescence compensation; 2) statistically- based analysis software that decreases the subjectivity of gating decisions; and 3) straightforward methods for developing and applying gating models that can be objectively applied within and across data sets. This current version still lacks important capabilities that w propose to add here. However, we have already started using it in our own laboratory and have distributed it to a limited group of flow users with good results. Following this trajectory, we pln to begin making this version available very soon at no charge to users at non-profit institutions (.edu, .org, .gov, etc.), and to keep the released version up-to-date as we add new capabilities in our laboratory. We request renewal funding here to enable us to complete aspects of this current technology and to add/improve several automated instrumentation and analysis functionalities that will significantly increase its scope and ease of use. The overall package wil facilitate flow cytometry work in all realms. However, it will offer particular benefits for HIV studies and for vaccine trials targeted at HIV and other diseases, since its robust automated utilities will simplify and speed access to statistically valid comparisons of changes induced in cytokine and other T cell subset markers in response to in vivo or ex vivo simulation by pathogens and their surrogates.