A Survey of Flow Cytometry Data Analysis Methods

摘要

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 neededto monitor the course and treatment of HIV infection, the evaluation of peripheral blood hematopoietic stem cellgrafts, and many other diseases. In practice, FCM data analysis is performed manually, a process that requires aninordinate 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 analysisapproaches using a framework introduced to report each of the components in a data analysis pipeline. Currentchallenges and possible future directions in developing fully automated FCM data analysis tools are also outlined.