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Where Are My Cells? 5 Reasons for Cell Loss During Flow Cytometry

Written by: Rachael Walker

last updated: June 18, 2026

If there are a million cells of interest in your sample and you pass them through a sorter, you might expect to get a million cells back. But you don’t – now what?

The golden rule of flow cytometry, especially cell sorting, is: ‘Put good cells in and get good cells out’.

When you sort, you might not get good cells out, and you may not get the numbers you were expecting. In this article, I’ll go over a few reasons why your cell numbers might be low after sorting.


1. Hardware aborts

A hardware abort occurs when an instrument can’t process the information about an event because it is still processing a previous event. This is also known an electronic abort. On analog machines, such as an Influx, it takes around 5 ?s to process an event, so if another event is detected in that time frame, both events are not processed and are aborted. This is usually less than 10% of events on an Influx. Instruments with digital electronics, such as the Aria, can process more than one event at a time leading to fewer aborts. Hint: Dilute your cells to a good cell concentration (between 10–20 million/ml) and make sure you filter your cells with the appropriate cell filter to prevent “stickiness.” This will help reduce hard aborts.

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2. Software Aborts

When sorting a cell, the user can define criteria for sorting based on the position of the cell within a droplet and the location of other events in adjacent droplets. If a droplet does not follow the criteria, than the event will not be counted. These are known as software aborts or coincidence aborts. These aborts occur to maintain purity in a sort; a droplet will be sent to waste if there is a risk it contains an unwanted event.


3. Sort modes/sort envelopes

There are different sort modes that can be selected; they have different names depending on the instrument, however they all work in basically the same way.

Sort Modes

Enrich/Yield mode: Used when cell number is more important than purity. This enriches a population by sorting all desired events regardless of its position in the droplet or whether there could be contaminating events in adjacent droplets. This mode is often used to quickly enrich a population before re-sorting using more stringent modes.

Purify mode: Used when high purity is wanted as well as high recovery being important. So a droplet is sorted if it contains a cell of interest but is aborted if there is a contaminating cell in an adjacent droplet. The mode is used for most sorting and efficiencies above 85% are common.

Single Cell mode: Used when it is important to sort only one cell and eliminate the possibility of sorting an empty drop. This mode means high purity, however there is a very high abort rate. This mode is used when sorting into 96 well plates and ensures that only one of the desired cells is sorted into a well.

Sort Envelopes

As well as selecting the sort mode, the user can define a sort envelope, which is the number of drops to which the sort mode will be applied (see Figure 1). For example, Enrich mode will sort the leading and trailing droplet as well as the target droplet. Although most purity mode sorts are sorted on Purify 1, which sorts only the droplet that contains the cell of interest, this can be modified to Purify 1–2, which will sort the leading or trailing droplet as well. As the cell of interest might not be in the centre of the droplet, this mode ensures its capture especially as the cell might move into another droplet. This mode does mean that your collection tube fills up quicker and the number of sorted events that the machine records will be higher than the actual number of events in your tube.

Slide1
Figure 1

When doing single cell sorting, it is common to use Single 0.5 mode, as this ensures that the cell has to be in the middle of the droplet for sorting. This means that you are more like to have a cell in your well but you can lose up to 10 cells of interest through aborts.


4. Poor Viability

As discussed in the article on how a sorter works, sorting has little effect on your cells. However, if they are poorly to start with, then they are unlikely to survive sorting.

It’s important to use a viability dye such as propidium iodide or DAPI when sorting, so you can determine the viability of the cells as they go into the machine. These dyes only go into cells with a compromised membrane so your healthy, happy cells won’t take up the dye and be affected. Your dying or dead cells will take up the viability dye and will show positive staining. Using a viability dye might clue you in to why you don’t get as many cells back.

5. Yield and recovery

Your yield and recovery factor into the number of cells you get back after a sort. And your purity will determine how successful the sort was. But these terms can often be confused. Let’s get them straight and talk about how they affect your cell numbers.

Purity

The purity of your cells is the percentage of cells of interest in your collection tube after they have been sorted. Purity is ascertained by running an aliquot of sorted cells back through the machine after you have finished your sort.

It will show if the required populations to be sorted have been sorted. You can also add a little bit of viability dye and determine the post-sorting viability.

Note: When checking the purity, you should start with your original gating scheme but, you may need to alter the gates slightly due to quenching/photo-bleaching of dyes and/or some osmotic and other changes.

Cells can often be sorted to above 95% purity, although with a distinct population that is being sorted, this can be above 99%.

Purity = Proportion of cells of interest/total number of cells in the sort tube

Yield

The yield of cells is the number of cells of interest in your sample tube compared to the number of cells of interest in your sorted tube. This number will be much lower, as you will lose cells during the sort due to aborts.

Yield = Proportion of sorted cells of interest/ total number of cells of interest in initial tube

Recovery

Recovery of cells is the number of cells that are in your collection tube compared to the number of cells that the sorter tells you are in the tube. It is usual to lose cells do to various reasons:

  • Cells moving out of droplets and subsequent sorting of empty drops
  • Cells sticking to the tubes
  • Cells dying during sorting
  • Sometime cells just leap out of the tubes!

After sorting you should expect around 70-80% recovery of your cells.

Recovery = Number of cells in sorting tube/number of cells that were sorted


Improve your yield and recovery

It is possible to improve the yield and recovery of your sorts.

  • Start with a nice sample preparation. Healthy, clump-free cells will give the best results.
  • Sort into collection media containing a protein source to help with recovery. A protein source such as fetal calf serum or bovine serum albumin dissolves the charge on the droplet and helps to stop cells sticking to the tube.
  • Use polypropylene collection tubes to keep cells from sticking to the sides of the tubes. Polystryene tubes (often used for analyzers) will hold the charge and you will have lower cell numbers in your tube.

As a general rule, if your tube contains 1 million happy healthy cells, then expect to get around half of those into your sorting tube. You might get more, but it’s always better to start with more cells than you think you will need.

Less can be more

Although it might be upsetting that you are not collecting all the cells you want, the machine is actually helping you out by ensuring that the cells in your collection tube are actually the cells you want. The sorters also allow flexibility to change stringency of sorts depending on your application.


You made it to the end—nice work! If you’re the kind of scientist who likes figuring things out without wasting half a day on trial and error, you’ll love our newsletter. Get 3 quick reads a week, packed with hard-won lab wisdom. Join FREE here.

Rachael has a PhD in Clinical Engineering from the University of Liverpool.

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