The Table Editor

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And the table editor is this latticework looking icon up in the static toolbar. Also again, available in the FlowJo tab, navigate band of actions, table editor, hot keys, command T. It'll open up a window that looks similar to the layout editor where you've got these plus and minus buttons in the top left-hand corner, you've got a few tabs, and different tools, and you can make as many tables as you want with the gated populations and statistics in your analysis.

What I'm going to do is just grab a few gates. I'm going to say let's do the CD8 positive T cell populations. Let's do CD4's and all of the gated frequencies for interfering gamma perforated art. If I drag and drop those highlighted populations from the workspace gating tree, into the table editor, it'll create a list of those gated populations along with the statistic that we're going to enumerate in my table here. I'm going double click and call this table CD8 Positive Basic Gates. Basic Stats.

In order to batch through all the samples in a given group here, what I'm going to do is set the group that I want to look at. First, I'm just going to set the all stain groups so it has twenty samples there. Then, I'm going to create the table, in this case, to just display. For now. Create the table. Creates a display table. It's got all of the samples in the group that I have selected here. What happens when you create an external table is that each row in the table editor becomes a column in the output. In the output, each row is a different sample contained within the workspace group that you have selected here under your iteration options.

A few things that bother me is that when you get really long gating trees, headers get really complex. Know that you can change the name by typing into this naming field a shortened, succinct name for your population. Maybe I just want to call this "CD8 Percent" for CD8 frequency. Then, the next one. "IFMG Percent." "Perf Percent." "P Irc Percent." And "CD4 Percent." Okay? Now, when I create this table, it shows those shortened name headers instead and makes it a little bit easier for me.

The other feature that I really want to show you is the Visualization Tools in the Table Editor that'll apply some sort of formatting to these numbers based on the distribution. If I want to apply a visual formatting to a statistic in my displayed table, I go to the Visualize tab in header ribbon and select the columns or the rows in this case that are going to become the columns in the output and I apply some sort of visualization feature. In this case, I'll just show you the heat map feature. When I click on that, it adds the heat map icon to that row and then when I go back to my table editor tab and bash report to display, creating that table, you can see that each column is now uniquely formatted with low numbers being displayed in a blue color and the high numbers highlighted in a yellow color. You can see the differences immediately in the different markers that we're looking at and how they respond in this assay. You can really see the variation between different samples more robustly in a visual format.

You can also do other options like visualize the standard deviation, the difference, how far away the numbers are away from the mean statistic, that's the summary statistic at the end of a table. If I create this table it either creates italicized, bold italicized, or even red bold italicized numbers. If you're greater than one, two, or three standard deviations away from this mean summary statistic of the column. It shows you how far away am I from the center.

Then, there's even a way to set up what we call expected ranges in your preferences. You know what's normal and you want to add a formatting only if that statistic goes above or below what you consider normal. You can set these expected ranges up in your Ranges tab of the Preferences pane and define whatever frequency or median or florescence MFI range that you might want to apply and then apply those and then get different formatting for that. I find that the heat map is just a great way to start looking at your data when you create your table. Oh, I turned it off there, so let's do it again. Apply the heat map instead of remove it. Then, push that table out to display.

If I want to get these numbers outside of FlowJo I can either command A, copy and paste them into an Excel document or a Google Sheets, or any other spreadsheets program. There's my table just with a copy and paste. You can also change the display here when you create your table. Instead of going to a display you can push this to a different type of file and make a text file, a comma separated values text, an Excel document, a SQL database file, or an HTML formatted image. The HTML image will actually create a link to your table with the color formatting. If you do a text or an Excel file it'll just create the file. Here, I'm going to do it on my desktop.

I'm going to create a text file that'll be called CD8 Positive Basic Gates with a click of the cog button. Then, if I go to my desktop, there is the text file that I just created and I can go ahead and open that up in Excel and it'll show me all of the numbers. At that point, I can use the graphing features in Excel or some other graphing program to make bar charts and display the differences between different groups of patients or different STEM conditions and so on.

That is the basic work flow through FlowJo is that we will bring data in, create a gating tree or a gating hierarchy on a sample, apply it to a number of samples that we want to compare the phenotype or functional responses between, go to my layout editor to create a beautiful gating hierarchy layout showing the responses or other phenotypes that are of interest in that panel that I've stained these cells with. Then, once I'm happy with all the gating, after reviewing the gates on every sample, I can generate the finalized list of statistics through the table editor, that then can be used externally.