FlowCore: a Bioconductor Package for High Throughput Flow Cytometry

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2009 Apr 11

PMID 19358741

Citations 296

Authors

Florian Hahne

Nolwenn LeMeur

Ryan R Brinkman

Byron Ellis

Perry Haaland

Deepayan Sarkar

Josef Spidlen

Errol Strain

Robert Gentleman

Affiliations

Soon will be listed here.

Abstract

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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