We do a lot of flow cytometry in the lab. Inevitably, what ends up being the most practical tool for analysis of low cytometry data is FlowJo. While I’ve been using FlowJo for a long time, I realize it isn’t super intuitive and new people to the lab may first struggle in using it. Thus, here’s a short set of instructions for using it to do a basic process, such as determining what percentage of live cells are also GFP positive.
Obviously, if you don’t have FlowJo yet, then download it from the website. Next, log into FlowJo Portal. I’m obviously not going to share my login and password here; ask someone in the lab or consult the lab google docs.
Once logged in, you’ll be starting with a blank analysis workspace, as below.
Before you start dragging in samples, I find it useful to make a group for the specific set of samples you may want to analyze. Thus, I hit the “Create Group” button and type in the name of the group I’ll be analyzing.
Now that the group is made, I select it, and then drag the new sample files into it, like below:
Now to actually start analyzing the flow data. Start by choosing a representative sample (eg. the first sample), and double clicking on it. By default, a scatterplot should show up. Set it so forward scatter (FSC-A) is on the X-axis, and side scatter (SSC-A) is on the Y-axis. Since we’re mostly using HEK cells, that means that main thing we will be doing in this screen is gating for the population of cells while excluding debris (small FSC-A but high SSC-A). Thus, make a gate like this:
Once you have made that gate, you’ll want to keep it constant between samples. Thus, right click on the “Live” population in the workspace and hit “Copy to Group”. Once you do that, the population should now be in bold, with the same text color as the group name.
Next is doublet gating. So the live cell population will already be enriched for singlets, but having a second “doublet gating” step will make it that much more pure. Here is the best description of doublet gating I’ve seen to date. To do this, make a scatterplot where FSC-A is on the X-axis, and FSC-H is on the Y-axis. Then only gate the cells directly on the diagonal, thus excluding those that have more FSC-A relative to FSC-H. Name these “Singlets”.
And like before, copy this to the group.
Next is actually setting up the analysis for the response variable we were looking to measure. In this case, it’s GFP positivity, captured by the BL1-A detector. While this can be done in histogram format, I generally also do this with a scatterplot, since it allows me to see even small numbers of events (which would be smashed against the bottom of the plot if it were a smoothed histogram). Of course, a scatterplot needs a second axis, so I just used mCherry fluorescence (or the lack of it, since these were just normal 293T cells), captured by the YL2-A detector.
And of course copy that to the group as well (you should know how to do this by now). Lastly, the easiest way to output this data is to hit the Table Editor button near the top of the screen to open up a new window. Once in this window, select the populations / statistics you want to include from the main workspace, and drag it into the table editor, so you have something that looks like this.
Some of those statistics aren’t what we’re looking for. For example, I find it much more informative to have the singlets show total count, rather than Freq of parent. To do this, double click on that row, and select the statistic you want to include.
And you should now have something that looks like this:
With the settings fixed, you can hit the “Create Table” button at the top of the main workspace. This will make a new window, holding the table you wanted. To actually use this data elsewhere (such as with R), export it into a csv format which can be easily imported by other programs.
Congratulations. You are now a FlowJo master.