flowCore: a Bioconductor package for high throughput flow cytometry

被引：389

作者：

Hahne, Florian ^{[1
]}

LeMeur, Nolwenn ^{[1
,2
]}

Brinkman, Ryan R. ^{[3
]}

Ellis, Byron ^{[4
]}

Haaland, Perry ^{[5
]}

Sarkar, Deepayan ^{[1
]}

Spidlen, Josef ^{[3
]}

Strain, Errol ^{[5
]}

Gentleman, Robert ^{[1
]}

机构：

[1] Fred Hutchinson Canc Res Ctr, Dept Life Sci, Computat Biol Program, Div Publ Hlth Sci, Seattle, WA 98109 USA

[2] Univ Rennes 1, IRISA Symbiose, INSERM, EA SeRAIC, F-35042 Rennes, France

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

[4] AdBrite Inc, San Francisco, CA 94103 USA

[5] BD Biosci, Res Triangle Pk, NC 27709 USA

来源：

BMC BIOINFORMATICS | 2009年 / 10卷

基金：

美国国家卫生研究院;

关键词：

BIOINFORMATICS;

D O I：

10.1186/1471-2105-10-106

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Background: Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates. Results: We developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data. A key component of which is having suitable data structures that support the application of similar operations to a collection of samples or a clinical cohort. In addition, our software constitutes a shared and extensible research platform that enables collaboration between bioinformaticians, computer scientists, statisticians, biologists and clinicians. This platform will foster the development of novel analytic methods for flow cytometry. Conclusion: The software has been applied in the analysis of various data sets and its data structures have proven to be highly efficient in capturing and organizing the analytic work flow. Finally, a number of additional Bioconductor packages successfully build on the infrastructure provided by flowCore, open new avenues for flow data analysis.

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