Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.
Elucidation of seventeen human peripheral blood B-cell subsets and quantification of the tetanus response using a density-based method for the automated identification of cell populations in multidimensional flow cytometry data.
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使用基于密度的方法对多维流式细胞仪数据中细胞群体自动鉴定，阐明了十七个人外周血B细胞子集和破伤风反应的定量。
DOI：
10.1002/cyto.b.20554
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发表时间：
2010
影响因子：
3.4
通讯作者：
Scheuermann, Richard H.
中科院分区：
文献类型：
--
作者：
Qian, Yu;Wei, Chungwen;Lee, F. Eun-Hyung;Campbell, John;Halliley, Jessica;Lee, Jamie A.;Cai, Jennifer;Kong, Y. Megan;Sadat, Eva;Thomson, Elizabeth;Dunn, Patrick;Seegmiller, Adam C.;Karandikar, Nitin J.;Tipton, Christopher M.;Mosmann, Tim;Sanz, Inaki;Scheuermann, Richard H.
多参数流式细胞术(FCM)的进步现在允许独立检测单个细胞上更多数量的荧光染料，产生越来越高维度的数据。这些数据的复杂性增加，使得使用基于单色或双色显示的传统手动门控策略从高维FCM数据中识别细胞群变得困难。为了解决这一挑战，我们开发了一个新的程序，FLOCK(Flow Cluging Without K)，它使用基于密度的聚类方法，以无偏见的方式从多个样本中通过算法识别生物相关的细胞群，从而消除了依赖于操作员的可变性。FLOCK被用来客观地鉴定人类外周血样本中17个不同的B细胞亚群，并鉴定和量化外周血中对破伤风和其他疫苗有瞬时反应的新的浆母细胞亚群。Flock已在公众可用的免疫学数据库和分析门户网站Immport(http://www.immport.org))中实现，供免疫学研究界开放使用。Flock能够通过客观、自动化的计算方法，在使用多参数流式细胞术的实验中识别细胞亚群。使用像FLOCK这样的算法进行FCM数据分析，消除了识别和量化细胞子集的主观和劳动密集型人工选通的需要。通过这些计算方法识别的新种群可以作为进一步实验研究的假设。
Advances in multi-parameter flow cytometry (FCM) now allow for the independent detection of larger numbers of fluorochromes on individual cells, generating data with increasingly higher dimensionality. The increased complexity of these data has made it difficult to identify cell populations from high-dimensional FCM data using traditional manual gating strategies based on single-color or two-color displays. To address this challenge, we developed a novel program, FLOCK (FLOw Clustering without K), that uses a density-based clustering approach to algorithmically identify biologically relevant cell populations from multiple samples in an unbiased fashion, thereby eliminating operator-dependent variability. FLOCK was used to objectively identify seventeen distinct B cell subsets in a human peripheral blood sample and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations in peripheral blood. FLOCK has been implemented in the publically available Immunology Database and Analysis Portal – ImmPort (http://www.immport.org) for open use by the immunology research community. FLOCK is able to identify cell subsets in experiments that use multi-parameter flow cytometry through an objective, automated computational approach. The use of algorithms like FLOCK for FCM data analysis obviates the need for subjective and labor intensive manual gating to identify and quantify cell subsets. Novel populations identified by these computational approaches can serve as hypotheses for further experimental study.
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影响因子：
4.4
作者：
Bohnhorst, JO;Bjorgan, MB;Thompson, KM
通讯作者：
Thompson, KM
影响因子：
5.4
作者：
Agematsu, K;Nagumo, H;Komiyama, A
通讯作者：
Komiyama, A
影响因子：
3.4
作者：
Finn, William G.;Carter, Kevin M.;Hero, Alfred O.
通讯作者：
Hero, Alfred O.
影响因子：
3.7
作者：
Lo, Kenneth;Brinkman, Ryan Remy;Gottardo, Raphael
通讯作者：
Gottardo, Raphael
影响因子：
4.4
作者：
Lee, Jisoo;Kuchen, Stefan;Lipsky, Peter E.
通讯作者：
Lipsky, Peter E.