On multiparameter data analysis in flow cytometry

Authors


  • Research sponsored by the Office of Health and Environmental Research, U.S. Department of Energy, under contract DE-AC05-840R21400 with the Martin Marietta Energy Systems, Inc.

Abstract

Increasing numbers of parameters that are accessible to simultaneous measurement in flow cytometric instruments, combined with the extremely large sample sizes common in flow cytometry, make it necessary to examine methods of multivariate statistics for their applicability to problems of visualization and quantitative analysis of flow cytometric data. This article describes some approaches to dimensionality reduction that appear well suited for data sets obtained by flow cytometry.

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