The above images show data from a tissue digest. From this post, you should be able to identify if there are major issues with the instrument settings (which can only be fixed by re-recording the samples) or if the samples need to be cleaned up in analysis software with gates or a new compensation matrix. There are a lot of ways to get bad flow cytometry data – in this post I’ll focus on the reasons that I feel are the easiest to identify and fix. So in this post I’d like to go over some examples of bad data to assist novice flow cytometrists. It was just a skill that I eventually picked up. Looking back, I realized that no one really ever told me what bad data looks like. But for novice flow cytometrists this step of identifying problems can be very difficult. With baking this is easy for everyone, even a novice – you taste your food and immediately know it doesn’t taste good. The step that is often skipped is how to assess your results to identify problems.

Flow cytometry training materials usually focus on the protocol of how to perform a flow cytometry experiment, but they don’t always cover how to troubleshoot. As I created my flow cytometry training materials I realized that I didn’t cover all of these steps. It’s been a while since I learned flow cytometry, but baking bread reminded me of the process of learning a new skill: follow a protocol, assess the results and identify problems, determine how to fix the problems, and repeat the protocol with adjustments to address the problems. And while I learned to perfect my bread in my free time, I spent a lot of my working hours on training materials for new flow cytometrists – that’s when I started to realize some similarities between these two tasks. I decided to take on baking sourdough bread (like many other quarantined individuals). When the global pandemic hit and Chicago’s shelter in place orders prevented me from going into the lab, I started doing some experiments in my kitchen instead.

Flowjo 10 compensation tutorial