flowCore: a Bioconductor package for high throughput flow cytometry
Fred Hutch Cancer Center · Inserm · +8 more institutions
Abstract
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.
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.
Citation impact
- FWCI
- 5.48
- Percentile
- 100%
- References
- 16
Authors
9- FHFlorian HahneCorresponding
Fred Hutch Cancer Center
- NLNolwenn Le Meur
Inserm, Institut de Recherche en Informatique et Systèmes Aléatoires, Fred Hutch Cancer Center, Université de Rennes
- RRRyan R. Brinkman
BC Cancer Agency, Terry Fox Research Institute
- BEByron Ellis
CBRITE (United States)
- PHPerry Haaland
Research Triangle Park Foundation, BD Biosciences (United States), BD Technologie (United States)
Topics & keywords
- Bioconductor
- Computer science
- Software
- Data mining
- Data management
- Throughput
- Automation
- Data science
- Industry, innovation and infrastructure