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Advances in Bioinformatics
Volume 2009 (2009), Article ID 193947, 11 pages
Research Article

FlowFP: A Bioconductor Package for Fingerprinting Flow Cytometric Data

Department of Pathology and Laboratory Medicine, School of Medicine, University of Pennsylvania, 207 John Morgan Bldg., Philadelphia, PA 19104-6082, USA

Received 1 April 2009; Accepted 18 June 2009

Academic Editor: Raphael Gottardo

Copyright © 2009 Wade T. Rogers and Herbert A. Holyst. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new software package called flowFP for the analysis of flow cytometry data is introduced. The package, which is tightly integrated with other Bioconductor software for analysis of flow cytometry, provides tools to transform raw flow cytometry data into a form suitable for direct input into conventional statistical analysis and empirical modeling software tools. The approach of flowFP is to generate a description of the multivariate probability distribution function of flow cytometry data in the form of a “fingerprint.” As such, it is independent of a presumptive functional form for the distribution, in contrast with model-based methods such as Gaussian Mixture Modeling. FlowFP is computationally efficient and able to handle extremely large flow cytometry data sets of arbitrary dimensionality. Algorithms and software implementation of the package are described. Use of the software is exemplified with applications to data quality control and to the automated classification of Acute Myeloid Leukemia.