Revealing the Precision of Your Manual Cell Counts
– 8 min read
Have you ever repeated your cell count only to get a very different result the second time around? When this happens, it can leave you paralyzed, questioning your data, and unable to make decisions about your cell culture or future experiments.
In all areas of science, ‘precision’ (or repeatability) can make or break experiments. Unfortunately, manual cell counting is particularly prone to random errors and, as a result, often suffers from low precision. But if you find yourself questioning the precision of your results, don’t panic; there are plenty of things you can do to improve the repeatability of your cell counts.
In this blog post, we cover:
- How you can measure the precision of your cell counts
- The most common sources of error in manual cell counting
- How you can increase precision in cell counting
How Do We Measure Precision in Cell Counting?
If you aren’t sure if your cell counts are up to scratch, you can check their precision by repeating your measurements and calculating the standard deviation (σ) and coefficient of variation (CV) of your results.
You can calculate your standard deviation, which shows the dispersion of your results around the mean, using the following formula:1
A low standard deviation indicates that your cell counts do not vary much from the mean, i.e., you have repeatedly consistent cell counts, indicating high precision.
Once you have determined the standard deviation of your results, you can also calculate CV. This is the most common parameter used to indicate the precision of cell counts and it is typically expressed as a percentage. You can calculate CV using the following formula:
Experienced manual cell counters usually aim for a CV in the range 5 – 15%. If your CV is much higher, you might want to investigate how you can improve your cell counting procedures and increase your precision.
A Step-By-Step Guide to Validating Your Cell Count
If you are still in doubt about your cell counts, or you are working in a good manufacturing practice (GMP) environment, you need to validate your procedures. Validation demonstrates how accurate, precise, and robust your processes are and proves your methodology is fit for purpose. It typically involves conducting a range of experiments, including linearity studies, to investigate your precision across a range of concentrations.
If you want to learn more about validating your cell counting methods, watch our webinar ‘How Precise Are Your Cell Counts?: A Guide to Validating a Cell Counting Method’.
What Are the Major Sources of Error in Manual Cell Counting?
Manual cell counting with a hemocytometer is often error-prone. Typical errors can be as high as 20 – 30%,2 and low precision is one of the major disadvantages of using a hemocytometer. Identifying which sources of error are impacting your results is the first step in increasing your precision and reducing your CV.
We outline four major factors affecting cell counting precision below:
1. Human Error During Sample Preparation
Like all procedures that rely on manual preparation, cell counting with a hemocytometer is susceptible to human error from various sources, including imprecise pipetting, errors in dilution, and poor mixing.3
Errors can also arise from overloading the hemocytometer chambers. Though the hemocytometer contains a fixed volume, the space between the counting chamber and the cover glass can increase slightly if you overfill the chamber with liquid. Overcharging the counting chamber results in underestimating the sample volume and overestimating your cell concentration.
2. Subjectivity During the Counting Process
Differentiating between cells and debris or other particles can be tricky, even for the trained eye. If you cannot distinguish between cells and debris easily, your cell count might be artificially high.
It can also be challenging to tell whether a cell is inside or outside a counting grid. As a result, manual cell counting can be subjective, and the final count can depend on the operator. A recent publication by Manzini et al. showed that even when operators are highly experienced in cell counting, inter-operator variation can reach nearly 20%.4
3. Inconsistencies in Cell Staining
Trypan blue is one of the most widely used dyes in manual cell counting. It is a membrane-impermeable dye that only stains non-viable cells with damaged cell membranes. However, trypan blue doesn’t stain cells uniformly. This causes inconsistencies in cell counts because it can be challenging to differentiate lightly stained non-viable cells from viable ones.
Trypan blue is also toxic to cells, so your dead cell count may be higher if you leave more time between staining and counting. Furthermore, because trypan blue is a salt it can cause changes in cellular osmoregulation, which can make cells burst, artificially lowering the total and dead cell count and leading to an overestimation of cell culture viability.
This webinar tells you more about how trypan blue can affect cells.
4. Calculation Errors
Manual cell counting relies on several calculations, including working out the dilution factor, total cell count or concentration, viability, standard deviation, and CV. As with all calculations, there is the potential for human error to creep in when noting down data or performing calculations. Significant errors are typically easy to identify, but more minor errors (is the last digit a 1 or a 7?) can go unnoticed and impact the precision of your final results.
How to Increase Precision in Cell Counting
Once you know where your errors are coming from, you can start reducing or eliminating them to increase your overall precision.
Working carefully and consistently can reduce the effects of human error. Take special care when filling the hemocytometer to ensure you do not overfill the chamber.
The impact of subjectivity in the counting process can be reduced by increasing the number of chambers you count and performing duplicate or triplicate cell counts to validate your results. If you decide to perform repeat measurements, make sure you take a new aliquot of cells, mix them with your chosen dye and re-load the chamber, rather than just re-count the cells or re-load your chamber with a second sample that is already stains. This will give you the most representative repeat measurement.
The more cells you count, the smaller the effects of random errors and the more precise your results will be. As a general rule, you should count at least 400 cells per sample (for more information, see our tech note ‘Effects of sample concentration on cell counting variation’).
You can reduce the variation between different users by agreeing on cell counting rules and applying them consistently. For more information about cell counting rules and procedures, see ‘Spilling the Secrets: How to Count Cells with a Hemocytometer.’
You can reduce the chance of calculation errors by automating your calculations. For example, you could use our downloadable cell counting spreadsheet, which calculates your dilution factor, total cell count, viability, standard deviation, and CV. By using this sheet, you can eliminate errors in calculations, and you’ll no longer need to worry about whether you hit the ‘5’ or the ‘6’ key on your calculator.
Download the cell counting tool from ChemoMetec.
Switching to Automated Cell Counting
If you are experiencing problems with the precision of your cell counts, you could consider using an automated cell counter. Automated processes eliminate errors by applying counting protocols consistently every time. Furthermore, they count large numbers of cells quickly, minimizing the effects of random errors. Some automated counters also use fluorescent dyes instead of trypan blue, removing the issues associated with inconsistent staining and toxicity.
The graphs below show the precision of manual counting vs. automated counting at a range of cell concentrations. Graphs A and B show CV as a function of the cell concentration for A) automated cell counting using the NucleoCounter® NC-202™, and B) manual cell counting using a hemocytometer.5
In graph A, most of the data points are located either on or close to the fitted curve (the mean), indicating low variance and high precision. In graph B, the data points are scattered, and only a few are located on the fitted curve, indicating low precision. Furthermore, although both the automated and the manual cell counting methods show an increase in CV at lower cell concentrations due to increased contributions from random errors, the increase is lower when cells are counted with an automated counter.
Comparing the two graphs makes it apparent that automated cell counting offers better precision than manual counting. In fact, using an automated cell counter can double your cell counting precision compared with using a hemocytometer and manual cell counting.5
Contact us to learn more about automated cell counting solutions or sign up to our newsletter to make sure you don’t miss our next blog post.
- Webinar: How Precise Are Your Cell Counts?
- Tech note: NucleoCounter® NC-202™ Performance Data
- Webinar: Why is Trypan Blue Toxic and Unsafe to Use?
- Blog post: Spilling the Secrets: How to Count Cells with a Hemocytometer
- Blog post: Why Didn’t My Manual Cell Counting Always Work?
- Blog Post: Manual vs automated cell counting
- Ross, S. M. (2014). Introduction to Probability and Statistics for Engineers and Scientists (Fifth Edition), Chapter 2. Academic Press.
- Electron Microscopy Sciences: Neubauer Haemocytometry.
- Biggs, R. et al. (1948). The Errors of Some Haematological Methods as They Are Used in a Routine Laboratory. Journal of Clinical Pathology, 1(5):269-287.
- Manzini, P. et al. (2022). Validation of an automated cell counting method for cGMP manufacturing of human induced pluripotent stem cells. Biotechnology Reports, 33:e00708.
- ChemoMetec: Tech Note: NucleoCounter® NC-202™ Performance Data.
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