The author has a financial interest in FlowJo, one of the software packages discussed in this report.
Communication to the Editor
Article first published online: 12 JAN 2011
Published 2011 Wiley-Liss, Inc.
Cytometry Part A
Volume 79A, Issue 2, pages 95–101, February 2011
How to Cite
Roederer, M. (2011), Interpretation of cellular proliferation data: Avoid the panglossian. Cytometry, 79A: 95–101. doi: 10.1002/cyto.a.21010
This article is a US government work and, as such, is in the public domain in the United States of America.
- Issue published online: 24 JAN 2011
- Article first published online: 12 JAN 2011
- Manuscript Accepted: 20 NOV 2010
- Manuscript Revised: 11 NOV 2010
- Manuscript Received: 13 OCT 2010
- National Institute for Allergy and Infectious Diseases, NIH
- mathematical modeling;
- precursor frequency;
- cell division
There are several statistics that may be calculated to characterize a cellular proliferation experiment. By far, the most commonly-reported statistic is the percent of cells in the final culture that have divided; however, this statistic has significant limitations. Other statistics provided by software modeling provide a much richer characterization of the biological response; however, their use also comes with caveats. Here, I discuss the practical application of these statistics, including their limitations and interdependencies, using hypothetical data. The goal of this perspective is to prevent the blind reliance or overly optimistic (“panglossian”) interpretation of the statistics generated by software, so that researchers and reviewers have a more-informed basis for drawing conclusions from the data. Published 2011 Wiley-Liss, Inc.