Volume 2 / Issue 2

# Facility News

 Hi all,
 Summer is upon us and according to the prevision, it will be a very hot ☀️ and stormy 🌩️season ! What a better way to protect yourself than to spend more time in our analysers room which is always in some sort of winter ❄️ level cold zone ? Always look at the bright side in every situation 😉
 This month, in FACS Tips we are answering a recurring question in our facility : Is my population real ? We often have to discuss with users about it and we will provide here an explanation so you can be confident your data is revelant.
 The May Newsletter Quiz has been won by Marco Ongaro from the Verdeil Lab, congratulations !
 He correctly answered the first 3 questions (CD32, HBSS and True) and estimated FACS Flow usage for April at 717 L while the correct answer was 660 L ! Good job !
 Do you want to win this tasty FCF Toblerone ? Please find the questions for this month Quiz at the end of the Newsletter !
 Finally, I would like to remind everyone that the past FCF Newsletters are always available on the website at this location.
 See you next time ! 🙏

# FACS Tips

## How many events do I need to record?

 When performing a flow cytometry experiment, often samples are just run to completion. However, much is there is how much we record. While this is often the safest approach to an experiment, it is unprecise and can come with some downsides. More often this will give us much more than we need, meaning we use an unnecessary amount of machine time, and slow ourselves down with larger than needed file sizes. It is also possible that we may be under sampling and need to scale up the number of cells in each tube to make more precise repeatable experiments. This decision of how many cells to record can be advised by looking at the Poisson distribution of our sample.
 The Poisson Distribution
 The Poisson distribution, in statistics, is a probability distribution that is used to predict how many times an event is likely to happen over a specified period of time when we are given the average number of times that event occurred in the time period. While this may sound intimidating it is actually quite simple to calculate.
 To determine the number of events to be recorded in our target population for our experiment, we can just focus on the equation below. From this value we can also determine the estimated number of total events it will take to achieve this value.

### CV Coefficient of Variance is the quotient between SD and mean and represents the precision/reproducibility of the experiment

 Now the challenge is to determine what is your appropriate CV value to aim for. Because CV is a product to the standard deviation (SD) divided by the mean, as we increase the mean (number of events in our target population), our CV value goes down. This is important as it represents increased precision and reproducibility of our experiment. If our goal is to lower the CV, then that means we just need to increase the number of events in our final population of interest. So, if we start out with a chosen CV of say 5% (like in the example above), we know that we need to record 400 events in our population of interest. And if the frequency of the population is only 0.1% of the total events, then we need to record an estimated 400,000 events to get there.