Rapid Cell Population Identification in Flow Cytometry Data

被引：153

作者：

Aghaeepour, Nima ^{[2
,3
]}

Nikolic, Radina ^{[2
,4
]}

Hoos, Holger H. ^{[5
]}

Brinkman, Ryan R. ^{[1
,2
]}

机构：

[1] Univ British Columbia, Dept Med Genet, Vancouver, BC V5Z 1M9, Canada

[2] BC Canc Agcy, Terry Fox Lab, Vancouver, BC, Canada

[3] Univ British Columbia, Dept Bioinformat, Vancouver, BC V5Z 1M9, Canada

[4] Univ Oxford, Dept Stat, Oxford OX1 3TG, England

[5] Univ British Columbia, Dept Comp Sci, Vancouver, BC V5Z 1M9, Canada

来源：

CYTOMETRY PART A | 2011年 / 79A卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

flow cytometry; data analysis; cluster analysis; model selection; bioinformatics; statistics; AUTOMATION; REDUCTION;

D O I：

10.1002/cyto.a.21007

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

We have developed flowMeans, a time-efficient and accurate method for automated identification of cell populations in flow cytometry (FCM) data based on K-means clustering. Unlike traditional K-means, flowMeans can identify concave cell populations by modelling a single population with multiple clusters. flowMeans uses a change point detection algorithm to determine the number of sub-populations, enabling the method to be used in high throughput FCM data analysis pipelines. Our approach compares favorably to manual analysis by human experts and current state-of-the-art automated gating algorithms. flowMeans is freely available as an open source R package through Bioconductor. (C) 2010 International Society for Advancement of Cytometry

引用

页码：6 / 13

页数：8

共 26 条

[21] Automated high-dimensional flow cytometric data analysis [J].

Pyne, Saumyadipta ;

Hu, Xinli ;

Wang, Kui ;

Rossin, Elizabeth ;

Lin, Tsung-I ;

Maier, Lisa M. ;

Baecher-Allan, Clare ;

McLachlan, Geoffrey J. ;

Tamayo, Pablo ;

Hafler, David A. ;

De Jager, Philip L. ;

Mesirov, Jill P. .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (21) :8519-8524

[22]

Rosenberg A., 2007, P 2007 JOINT C EMP M, P410, DOI DOI 10.7916/D80V8N84

[23] Flow cytometric parameters with little interexaminer variability for diagnosing low-grade myelodysplastic syndromes [J].

Satoh, Chikako ;

Dan, Kazuo ;

Yamashita, Taishi ;

Jo, Risa ;

Tamura, Hideto ;

Ogata, Kiyoyuki .

LEUKEMIA RESEARCH, 2008, 32 (05) :699-707

[24]

Scott D. W., 1992, MULTIVARIATE DENSITY

[25]

Van Blerk M, 2003, CLIN CHEM LAB MED, V41, P323

[26] Data reduction for spectral clustering to analyze high throughput flow cytometry data [J].

Zare, Habil ;

Shooshtari, Parisa ;

Gupta, Arvind ;

Brinkman, Ryan R. .

BMC BIOINFORMATICS, 2010, 11

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