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Advances in Bioinformatics
Volume 2009 (2009), Article ID 584603, 19 pages
Review Article

A Survey of Flow Cytometry Data Analysis Methods

Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada V5Z 1L3

Received 1 May 2009; Revised 20 July 2009; Accepted 22 August 2009

Academic Editor: George Luta

Copyright © 2009 Ali Bashashati and Ryan R. Brinkman. 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.


Flow cytometry (FCM) is widely used in health research and in treatment for a variety of tasks, such as in the diagnosis and monitoring of leukemia and lymphoma patients, providing the counts of helper-T lymphocytes needed to monitor the course and treatment of HIV infection, the evaluation of peripheral blood hematopoietic stem cell grafts, and many other diseases. In practice, FCM data analysis is performed manually, a process that requires an inordinate amount of time and is error-prone, nonreproducible, nonstandardized, and not open for re-evaluation, making it the most limiting aspect of this technology. This paper reviews state-of-the-art FCM data analysis approaches using a framework introduced to report each of the components in a data analysis pipeline. Current challenges and possible future directions in developing fully automated FCM data analysis tools are also outlined.