The Importance Of Quality Control And Quality Assurance In Flow Cytometry (Part 4 Of 6)

Incorporating quality control as a part of the optimization process in  your flow cytometry protocol is important. Take a step back and consider how to build quality control tracking into the experimental protocol.  When researchers hear about quality control, they immediately shift their attention to those operating and maintaining the instrument, as if the whole weight of QC should fall on their shoulders.  

It is true that core facilities work hard to provide high-quality instruments and monitor performance over time so that the researchers can enjoy uniformity in their experiments.

That, however, is just one level of QC.  As the experimental results are critical for the researcher’s long-term goals therefore they should not be so laissez-faire with QC. Instead, they should jump in with gusto to not only understand what those managing the instruments are doing, but also to develop specific QC protocols for their experiment. This should ideally be done during the optimization phase.  

1. Instrument Quality Control 

Instrument quality control is designed to ensure that the instrument is performing consistently over time. It is extremely important to perform this each time prior to instrument use.   The instrument vendor will have their own recommendations for the daily QC. These directions are useful as if there are issues you can communicate with the vendor as you are providing them with information they expect.  

Generally this is run when the instrument is first turned on.  In many cases, it is worth performing at least a quick clean before starting the QC protocols. If you are a user who has access outside the normal hours of the instrument, it might be worth learning the QC protocols for yourself so that you can perform this necessary step before starting with your samples. A little QC goes a long way to making sure the instrument is behaving properly. 


Figure 1: Levey-Jennings plot of voltage over time

Another  important thing to remember is that while performing QC, make sure to examine the data, not just the pass/fail for the day, but the trends over the past week or month. Looking at how the data changes over time provides valuable insight into the stability of the instrument. 

One of the most common ways to do this is to use the Levey-Jennings plot. In this plot, the cumulative data is plotted over time, with the mean, and  +/- 2 (sometimes 3) standard deviations are overlaid. The user can see if the data they generated falls inside or outside of these control points.

It is pivotal to establish rules as  when to intervene based on the data. The most common rules are called the Westgard rules, which specify when a process is out of control. In these cases, the process must be stopped and the process corrected. In the case of an instrument, this could be as simple as cleaning the instrument, or as complex as requiring a service call due to a bad part. 

2. Voltage Control

If you have gone through the trouble of finding the optimal voltage for your specific experiment, it is worth the time to ensure that you maintain that intensity throughout the experiment. There are a variety of ways to do this, but one of the easiest is to use a bead to track the fluorescent intensity over time. The advantage of a bead is its consistency and traceability. You can order a given lot and use it for a longer period of time. 

Of course, this means you need to set up your own tracking sheets, so that when you sit down at the flow cytometer.  This way when you start working with the instrument, you can pull this sheet up, and run your bead control. This will let you both monitor the voltages and adjust it to hit the target values.  An example of such a sheet is shown below. 

Figure 2:  A QC tracking sheet. 

With this, you will also need to export the appropriate values. In this case since you’re focusing on the MFI of the bead, you would use tracking voltage change in your Levey-Jennings plot.  Any time you see significant issues (a major change greater than some percentage you define), it’s worth checking with the operators of the system to see if anything may have changed – new laser, new flow cell or the like

When you are coming to the end of the beadlot you are using, it’s time to order a new lot and perform an overlapping experiment.  In this experiment,  you run the old lot and the new lot at the same time, so that you can define the new target values, as shown below.

Figure 3 : Overlap experiment between old and new beadlot. 

In this case, the old bead lot has a mean fluorescent intensity of ~30,000.  The new beadlot has an MFI of ~49,000.  Thus, in your QC data, you would make a note of this, as well as the date when you transitioned over to the new value. 

3. Reference Control


The third control to evaluate during development is the reference control. The reference control is a known sample that will behave in a defined way in your panel. This could either be frozen PBMCs, a cell line, or a mixture of different cells – but something that you can standardize.  Each time you run an experiment, you take this reference control out and take it through the same process as the experimental sample. In doing so, this provides you with a control for the process of staining. This assures the researcher that the process worked, and that nothing was missing. It also provides a good check point – again running this before you run your sample will show if there are issues, allowing you to pause and troubleshoot before putting your valuable sample in the instrument. 

Concluding Remarks

During the optimization process of panel development, determining the important quality control metrics that need to be tracked is essential. These values are going to help determine if the data you generate is consistent and reproducible, as well as alert you to trouble on the instrument before you begin running your precious samples. While QC may not be as exciting as the actual data generation process, it is exceedingly important to ensure the quality of your data. 

To learn more about important control measures for your flow cytometry lab, and to get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.

Join Expert Cytometry's Mastery Class

ABOUT TIM BUSHNELL, PHD

Tim Bushnell holds a PhD in Biology from the Rensselaer Polytechnic Institute. He is a co-founder of—and didactic mind behind—ExCyte, the world’s leading flow cytometry training company, which organization boasts a veritable library of in-the-lab resources on sequencing, microscopy, and related topics in the life sciences.

Tim Bushnell, PhD

Similar Articles

The Power Of Spectral Viewers And Their Use In Full Spectrum Flow Cytometry

The Power Of Spectral Viewers And Their Use In Full Spectrum Flow Cytometry

By: Tim Bushnell, PhD

What photon from yonder fluorochrome breaks?  It is … umm… hmmm. Let me see. Excitation off a 561 nm laser, with an emission maximum of 692 nm. I’m sure if Shakespeare was a flow cytometrist, he might have written that very scene. But the play is lost in time. However, since the protagonist had difficulty determining what fluorochrome was emitting photons, let’s consider how this could be figured out. In my opinion, one of the handiest flow cytometry tools is the spectral viewer. This tool helps visualize the excitation and emission profile of different fluorochromes, as well as allowing you…

Fickle Markers: Solutions For Antibody Binding Specificity Challenges

Fickle Markers: Solutions For Antibody Binding Specificity Challenges

By: Tim Bushnell, PhD

Reproducibility has been an ongoing, and important, concept in the sciences for years.  In the area of biomedical research, the alarm was sounded by several papers published in the early 2010’s.  Authors like Begley and Ellis, Prinz and coworkers, and Vasilevsky and colleagues, among others reported an alarming trend in the reproducibility of pre-clinical data.  These reports indicated between 50% to almost 90% of published pre-clinical data were not reproducible.  This was further highlighted in the article by Freedman and coworkers, who tried to identify and quantify the different sources of error that could be causing this crisis.  Figure 1,…

5 Common Flow Cytometry Questions, Answered

5 Common Flow Cytometry Questions, Answered

By: Tim Bushnell, PhD

I want to thank all of you who send us your questions about flow cytometry, so I thought I would dip into the old email bag and answer a few of the common ones here.  If your question isn’t answered this time, look for it to be answered in a future blog post.  Of course, if you want us to cover a specific topic, drop us a line.  1. How Fast Can I Go? This is  a common question. The allure of the ‘hi’ button is hard to resist.  The faster you go, the sooner you are finished with data…

Combining Flow Cytometry With Plant Science, Microorganisms, And The Environment

Combining Flow Cytometry With Plant Science, Microorganisms, And The Environment

By: Tim Bushnell, PhD

My first introduction to flow cytometry was talking to a professor who’d brought one on a research cruise to study phytoplankton. It was only later that I was introduced to the marvelous world that’s been my career for over 20 years.   In that time, I’ve had the opportunity to work with researchers in many different areas, exposing me to a wide variety of cell types and more important assays. What continues to amaze me is the number of different parameters we can measure, not just the number of fluorochromes, but the information we can extract from samples – animal, vegetable…

Common Numbers-Based Questions I Get As A Flow Cytometry Core Manager And How To Answer Them

Common Numbers-Based Questions I Get As A Flow Cytometry Core Manager And How To Answer Them

By: Tim Bushnell, PhD

Numbers are all around us.  My personal favorite is ≅1.618 aka ɸ aka ‘the golden ratio’.  It’s found throughout history, where it has influenced architects and artists. We see it in nature, in plants, and it is used in movies to frame shots. It can be approximated by the Fibonacci sequence (another math favorite of mine). However, I have not worked out how to apply this to flow cytometry.  That doesn’t mean numbers aren’t important in flow cytometry. They are central to everything we do, and in this blog, I’m going to flit around numbers-based questions that I have received…

3 Must-Have High-Dimensional Flow Cytometry Controls

3 Must-Have High-Dimensional Flow Cytometry Controls

By: Tim Bushnell, PhD

Developments such as the recent upgrade to the Cytobank analysis platform and the creation of new packages such as Immunocluster are reducing the computational expertise needed to work with high-dimensional flow cytometry datasets. Whether you are a researcher in academia, industry, or government, you may want to take advantage of the reduced barrier to entry to apply high-dimensional flow cytometry in your work. However, you’ll need the right experimental design to access the new transformative insights available through these approaches and avoid wasting the considerable time and money required for performing them. As with all experiments, a good design begins…

The Fluorochrome Less Excited: How To Build A Flow Cytometry Antibody Panel

The Fluorochrome Less Excited: How To Build A Flow Cytometry Antibody Panel

By: Tim Bushnell, PhD

Fluorochrome, antibodies and detectors are important. The journey of a thousand cells starts with a good fluorescent panel. The polychromatic panel is the combination of antibodies and fluorochromes. These will be used during the experiment to answer the biological question of interest. When you only need a few targets, the creation of the panel is relatively straightforward. It’s only when you start to get into more complex panels with multiple fluorochromes that overlap in excitation and emission gets more interesting.  FLUOROCHROMES Both full spectrum and traditional fluorescent flow cytometry rely on measuring the emission of the fluorochromes that are attached…

Flow Cytometry Year in Review: Key Changes To Know

Flow Cytometry Year in Review: Key Changes To Know

By: Meerambika Mishra

Here we are, at the end of an eventful year 2021. But with the promise of a new year 2022 to come. It has been a long year, filled with ups and downs. It is always good to reflect on the past year as we move to the future.  In Memoriam Sir Isaac Newton wrote “If I have seen further, it is by standing upon the shoulders of giants.” In the past year, we have lost some giants of our field including Zbigniew Darzynkiwicz, who contributed much in the areas of cell cycle analysis and apoptosis. Howard Shapiro, known for…

What Star Trek Taught Me About Flow Cytometry

What Star Trek Taught Me About Flow Cytometry

By: Tim Bushnell, PhD

It is no secret that I am a very big fan of the Star Trek franchise. There are many good episodes and lessons explored in the 813+ episodes, 12 movies (and counting). Don’t worry, this blog is not going to review all 813, or even 5 of them. Instead, some of the lessons I have taken away from the show that have applicability to science and flow cytometry.  “Darmok and Jalad at Tanagra.”  (ST:TNG season 5, episode 2) This is probably one of my favorite episodes, which involves Picard and an alien trying to establish a common ground and learn…

Top Industry Career eBooks

Get the Advanced Microscopy eBook

Get the Advanced Microscopy eBook

Heather Brown-Harding, PhD

Learn the best practices and advanced techniques across the diverse fields of microscopy, including instrumentation, experimental setup, image analysis, figure preparation, and more.

Get The Free Modern Flow Cytometry eBook

Get The Free Modern Flow Cytometry eBook

Tim Bushnell, PhD

Learn the best practices of flow cytometry experimentation, data analysis, figure preparation, antibody panel design, instrumentation and more.

Get The Free 4-10 Compensation eBook

Get The Free 4-10 Compensation eBook

Tim Bushnell, PhD

Advanced 4-10 Color Compensation, Learn strategies for designing advanced antibody compensation panels and how to use your compensation matrix to analyze your experimental data.