Predicting the Best Resolution and Sensitivity in Panel Development and Reducing Inter-instrument Variability in Flow Cytometry

Predicting the Best Resolution and Sensitivity in Panel Development and Reducing Inter-instrument Variability in Flow Cytometry

Recorded On: 04/28/2015

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About the Presenters


Stephen Perfetto
Chief, Flow Cytometry Core Section

Stephen Perfetto received a BS in medical technology from the West Virginia University in 1977 and completed his MS in 1981 from West Virginia University. He studied and worked in the clinical blood bank and clinical immunology laboratories until 1988, when he joined the EPICS Division of Coulter Corporation. In 1990 he was recruited to the Walter Reed Army Institute of Research and was the manager of the core flow facility. While at WRAIR, he was involved in large HIV vaccine trials and developed functional to study the immune system of infected individuals.

In 2000 he joined the NIH in the department of the Vaccine Research Center (VRC) as a staff scientist and manager of the flow core facility. This facility is the world leader in multicolor flow cytometry and continues to actively develop this technology on a number of different fronts. One focus is on hardware development and reagent and analysis development. For several years, this lab has collaborated to develop Quantum Dots for use in immunophenotyping experiments.


James Wood, PhD
Flow Cytometry Consultant

James Wood obtained his BA in physics from Gettysburg College; however, he also availed himself to a broad range of general and advanced biology and chemistry courses during his undergraduate years. He completed his MS and PhD degrees in biophysics from The Pennsylvania State University studying the effects on the life cycle of cells after radiation exposure. In graduate school, he also developed the first microprocessor-based two-parameter flow cytometer data acquisition system. After completing a postgraduate position in the lab of Dr. Leon Wheeless at the University of Rochester Medical Center where he contributed to the development of a 3D slit-scan flow cytometer, he moved to Florida accepting a position with the EPICS Division of Coulter Corporation. He was manager of the New Products Research and Applications Laboratory during most of his tenure at Coulter and Beckman-Coulter. He currently consults for flow cytometry and pharmaceutical companies and manages the flow cytometry shared resource at Wake Forest University School of Medicine Comprehensive Cancer Center (WFUCCC).

Webinar Summary

Successful quantitative flow cytometry requires an understanding of the characteristics of a flow cytometer instrument that affect the measurement and analysis of the acquired photometric data. Flow cytometer instruments must be characterized before being used for critical work. The immediate goals include achieving better reproducibility of data, reducing variation and to facilitate intra/inter-lab comparisons of cytometry data. Characterization includes the determination of the instrument linearity, dynamic range, precision, accuracy, detection efficiency (Q), and electronic and optical noise (B). In particular, Q and B affect how well cellular receptors with low expression can be measured. For example, staining panels may be inadvertently designed to avoid measuring dim markers on PMTs with poor resolution. Unfortunately, current methods using bead sets to assess PMT resolution only provide rough estimates of Q and B. Thus, staining panel design and similar protocols remain a largely empirical process, requiring time and intimate experience with an instrument’s performance. Ascertaining these instrument characteristics are the first steps toward assessing how instruments can be standardized and calibrated. Ultimately, this may be part of the validation process to certify that a flow cytometer used for critical clinical and/or GMP work is performing at the required level needed to obtain accurate and precise results. Additionally, as part of this process we need to move from the common use of “relative intensity units (channel numbers)” to data measured and presented in physically relevant optical units (photons, photoelectrons, dye molecules, antibody binding sites).

Recently, James Wood (Wake Forest University) developed a new device, known as an LED Pulser, to measure B and Q directly and accurately. This device delivers consistent, uniform broad-spectrum light pulses, the amplitude of which can be adjusted with an electronic and/or an optical attenuator. Our presentation will demonstrate how this device is used to calculate Q and B values. In the past, data from multilevel bead sets have been used to facilitate comparisons of instrument sensitivity with Q and B; however, it has proved difficult to manufacture bead sets that have closely matched intrinsic CVs. In practice the LED Pulser, along with calibrated fluorochrome-loaded beads, can be used to determine the relationship between fluorescence channel numbers and the number of photoelectrons generated at the PMT photocathode (i.e., the statistical photoelectron estimate (Spe) using a weighted quadratic fitting of pulsed LED series data). This information, along with estimates of receptor density, can be used to calculate index values that provide quantitative guidance for panel design. Our presentation will describe this process step-by-step with examples. Additionally, we will show how the metrics can be used for inter-laboratory comparisons.

The first part of the webinar will present the principles behind the LED Pulser, as well as the appropriate use of the LED Pulser and how it compares to using multilevel bead sets for the calculation of Q and B. The second part of the webinar will introduce how the LED Pulser, along with calibrated fluorochrome-loaded beads lead to better estimates of the four facets of predictive panel design: (i) accurate Q and B values for each detector, (ii) optimal voltage settings, (iii) spillover/spreading error calculations, and (iv) estimates of receptor density and contribution to more quantitative determinations for optimizing panel design.

CMLE Credit: 1.0


Predicting the Best Resolution and Sensitivity in Panel Development and Reducing Inter-instrument Variability in Flow Cytometry
Recorded 04/28/2015
Recorded 04/28/2015 CYTO U Webinar presented by Steve Perfetto and Jim Wood, PhD
Open to download resource.
Open to download resource.
CMLE Evaluation Form
11 Questions
11 Questions CMLE Evaluation Form
Completion Credit
1.00 CMLE credit  |  Certificate available
1.00 CMLE credit  |  Certificate available