flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification

被引：88

作者：

Malek, Mehrnoush ^{[1
]}

Taghiyar, Mohammad Jafar ^{[1
]}

Chong, Lauren ^{[3
]}

Finak, Greg ^{[2
]}

Gottardo, Raphael ^{[2
]}

Brinkman, Ryan R. ^{[1
]}

机构：

[1] British Columbia Canc Agcy, Res Ctr, Terry Fox Lab, Vancouver, BC V5Z 1L3, Canada

[2] Fred Hutchinson Canc Res Ctr, Vaccine & Infect Dis Div, Seattle, WA 98109 USA

[3] Univ British Columbia, Bioinformat Training Program, Vancouver, BC V5Z 4S6, Canada

来源：

BIOINFORMATICS | 2015年 / 31卷 / 04期

基金：

美国国家卫生研究院;

关键词：

D O I：

10.1093/bioinformatics/btu677

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

flowDensity facilitates reproducible, high-throughput analysis of flow cytometry data by automating a predefined manual gating approach. The algorithm is based on a sequential bivariate gating approach that generates a set of predefined cell populations. It chooses the best cut-off for individual markers using characteristics of the density distribution. The Supplementary Material is linked to the online version of the manuscript.

引用

页码：606 / 607

页数：2

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