Data analysis and presentation in flow cytometry

被引：2

作者：

Khowawisetsut, Ladawan ^{[1
]}

Sukapirom, Kasama ^{[2
]}

Pattanapanyasat, Kovit ^{[2
]}

机构：

[1] Mahidol Univ, Siriraj Hosp, Fac Med, Dept Parasitol, Bangkok 10170, Thailand

[2] Mahidol Univ, Siriraj Hosp, Fac Med, Ctr Excellence Flow Cytometry,Dept Res & Dev, Bangkok 10170, Thailand

来源：

SCIENCEASIA | 2018年 / 44卷

关键词：

multivariate; statistics; univariate; CELL;

D O I：

10.2306/scienceasia1513-1874.2018.44S.019

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The advancement of flow cytometry technology together with a series of novel developments in hardware and software have facilitated both phenotypic and functional characterizations of different cell types. In addition, the availability of many monoclonal antibodies and an expanding range of dye-chemistry have made multi-parameter flow cytometry possible for simultaneous measurements of large numbers of cells with better information of complex cellular networks such as the immune system. Although it has the advantage of being a fast, objective and quantitative, but running polychromatic flow cytometry is a complex process with many challenges particularly in the data analysis. The purpose of this communication is to describe several types of presentation and analysis of both univariate and multivariate datasets.

引用

页码：19 / 27

页数：9

共 24 条

[1] Cryptococcus gattii Infection Dampens Th1 and Th17 Responses by Attenuating Dendritic Cell Function and Pulmonary Chemokine Expression in the Immunocompetent Hosts [J].

Angkasekwinai, Pornpimon ;

Sringkarin, Nuntarat ;

Supasorn, Oratai ;

Fungkrajai, Madtika ;

Wang, Yui-Hsi ;

Chayakulkeeree, Methee ;

Ngamskulrungroj, Popchai ;

Angkasekwinai, Nasikarn ;

Pattanapanyasat, Kovit .

INFECTION AND IMMUNITY, 2014, 82 (09) :3880-3890

[2]

[Anonymous], 2003, Practical flow cytometry

[3] Quantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry [J].

Chattopadhyay, Pratip K. ;

Price, David A. ;

Harper, Theresa F. ;

Betts, Michael R. ;

Yu, Joanne ;

Gostick, Emma ;

Perfetto, Stephen P. ;

Goepfert, Paul ;

Koup, Richard A. ;

De Rosa, Stephen C. ;

Bruchez, Marcel P. ;

Roederer, Mario .

NATURE MEDICINE, 2006, 12 (08) :972-977

[4] Good Cell, Bad Cell: Flow Cytometry Reveals T-cell Subsets Important in HIV Disease [J].

Chattopadhyay, Pratip K. ;

Roederer, Mario .

CYTOMETRY PART A, 2010, 77A (07) :614-622

[5] Flow cytometric immunophenotyping for hematologic neoplasms [J].

Craig, Fiona E. ;

Foon, Kenneth A. .

BLOOD, 2008, 111 (08) :3941-3967

[6] Microarray analysis of Mycobacterium tuberculosis-infected monocytes reveals IL26 as a new candidate gene for tuberculosis susceptibility [J].

Guerra-Laso, Jose M. ;

Raposo-Garcia, Sara ;

Garcia-Garcia, Silvia ;

Diez-Tascon, Cristina ;

Rivero-Lezcano, Octavio M. .

IMMUNOLOGY, 2015, 144 (02) :291-301

[7] FLUORESCENCE-ACTIVATED CELL SORTING [J].

HERZENBERG, LA ;

SWEET, RG ;

HERZENBERG, LA .

SCIENTIFIC AMERICAN, 1976, 234 (03) :108-117

[8] Interpreting flow cytometry data: a guide for the perplexed [J].

Herzenberg, Leonore A. ;

Tung, James ;

Moore, Wayne A. ;

Herzenberg, Leonard A. ;

Parks, David R. .

NATURE IMMUNOLOGY, 2006, 7 (07) :681-685

[9] Comparative Analysis of Genomic Signal Processing for Microarray Data Clustering [J].

Istepanian, Robert S. H. ;

Sungoor, Ala ;

Nebel, Jean-Christophe .

IEEE TRANSACTIONS ON NANOBIOSCIENCE, 2011, 10 (04) :225-238

[10] Relationships between IL-17+ Subsets, Tregs and pDCs That Distinguish among SIV Infected Elite Controllers, Low, Medium and High Viral Load Rhesus Macaques [J].

Khowawisetsut, Ladawan ;

Pattanapanyasat, Kovit ;

Onlamoon, Nattawat ;

Mayne, Ann E. ;

Little, Dawn M. ;

Villinger, Francois ;

Ansari, Aftab A. .

PLOS ONE, 2013, 8 (04)

← 1 2 3 →