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Limit / reduce the amount of events on the gating plot or normalize population event counts (slice of time)

Background

Sometimes dot plots get too crowded and you may want to limit or otherwise reduce the number of events for visual purposes while gating.

Alternatively, you may have an experiment with many samples, each one having different numbers of events, and you want to standardize the number of events across the samples for analysis.

Gating on the time channel of your FCS files can be a useful method for these situations. Click the links below to jump to sections in this article:

1) Limit / reduce the number of events on the plot while gating

2) Use the time gate to adjust or normalize the event count of existing populations

3) Use the time gate to adjust or normalize the event count of existing populations

Limit the number of events on the plot while gating

There isn't currently a special way, in the Cytobank platform, of limiting the number of events that are shown on the plot by a percentage or a slider bar. Instead, a gate will have to be drawn on the time channel. 

To "time slice" your data, first your experiment must have the time channel available in the corresponding file, then you need to navigate to the gating tab and change the X axis to time. You can select any marker as Y channel, but you will want to make sure the gate is tall enough to capture any variation within the Y dimension.

blobid4.png

(Time Sliced FCS-A gate. Example of gating time and then activating the gate to reduce events (TS). The gate is activated and deactivated serially (off screen) to show effect. The result is fewer events being shown on the scatter plot)

Note, you might have to adjust your scale settings to shrink or widen the overall time distribution.

Note, tailor the gate location per file to set the time gate to a unique location for different samples in your experiment.

Use the time gate to adjust or normalize event count of existing populations 

If you incorporated a time gate into your original gating strategy, then your populations will already be using it. However, if you have created the time gate after having already identified your population of interest, you will need to redefine your gating strategy to include the time gate. The beginning state of the population tree might look like this with the time gate outside the hierarchy:

 

blobid0.png

(a population manager with a time gate that is not part of any gating strategy)

 

You can visualize the corresponding Boolean expression by clicking on the Boolean expressions tab.

blobid1.png

To make the time gate part of the other populations, the Population tree and Boolean expressions tabs must be used. See the animation below for how the time gate in the example above is added to the definition of each existing population using the Boolean expressions:

 

GifForPopulationAssignment3.gif

(The population of interest gate is added to an existing time gating using the Boolean expressions) 

 

This could later be visualized using Sunburst View to monitor the population lineage. The image shows a time-sliced FCS-A gate in a light cyan.

 

blobid3.png

 

Clean up data acquired during a clog or period of abnormal machine behavior using time channel

Scanning the time channel of FCS files is a good practice to make sure the data were acquired consistently from the machine.

Using a polygon gate on the time channel is a useful way to gate out periods of an acquisition that have resulted in questionable data. The polygon allows for multiple slices of time with a single gate. See the example below for taking only prime segments of data. The PeacoQC algorithm can alternatively be used for punctuated data acquisition over the time. Another alternative is to use the Boolean expressions tab to combine the gates.

 

timeslice-polygon.png

 (Gate data on time with a polygon to take multiple slices of time in one gate
 

 *For Research Use Only. Not for use in diagnostic procedures.



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