Better Visualization of Cytoflex Data in Flowjo


-There are now 3 Beckman Coulter Cytoflex instruments on campus. These instruments have different detectors, electronics, software than what most people are used to, i.e., BD and FacsDiva.

-Flowjo default settings are generally set up to analyze data collected on BD instruments.

-Getting data from the Cytoflex instruments to be visualized properly may take some adjustments to settings you may not normally use.

-Presentation above has some Treg data that highlights the issues, and ways of correcting the visualization

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How bright are your fluorophores?

There are a few factors that get evaluated when designing immunophenotyping panels.

  1. Antigen density
  2. Brightness of fluorophore
  3. Fluorophore overlap (Compensation)
  4. Expression of protein (eg. is antigen A also expressed on the same cells as antigen B)

It takes a lot of experience to be able to put these all together. Over the last little while Tessa has been comparing a bunch of antibodies in order to help us have a more quantitative answer for “brightness of fluorophore”. She obtained roughly 45 of the same CD4 antibodies, but conjugated to different fluorophores. CD4 is relatively conserved from person to person (~50,000 molecules per cell) and can be useful for a longitudinal study like this. Below is a chart of Stain Index for each of these colors. Stain index is just a fancy way of calculating how separated the positive cells are from the negative cells. Most of it makes sense if you’ve paid attention to this kind of thing. One stand out is that BB515 is much brighter than FITC. Probably more expensive too but… We can and will use this data to also give us a more comprehensive understanding of “fluorophore overlap” but that still needs a bit of polishing. If you would like to play around with these FCS data files just let us know and we will send you a link to ubox.

Click on chart to enlarge

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UV Laser

I’ve been getting a lot of questions from folks about what dyes can and can’t be used together in the UV and Violet detectors. I’ve put together a little presentation that will hopefully shed some light on a few potential options that will make your life easier a little easier by incorporating the UV laser into your panels.

As always, let me know if you have any questions

James Marvin

UV presentation

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Impact of adjusting PMT voltages on Compensation

I am in the process of developing a training seminar specifically tailored for compensation. I came across this presentation and thought I would post it since it’s pretty darn good. It’s relatively complicated so if doesn’t make sense right away that’s ok. We will go over this material when the seminar is finished

Take home messages:
Voltages don’t make a difference for compensation, if the voltages are not to low. (Slide 7)

The impact of adjusting PMT voltages on spillover and compensation

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How many cells should I count?

Counting Statistics and the Poisson distribution

In the process of flow cytometry cells (events) are presented for analysis at random and their distribution will be described by Poisson statistics. Any sub-set of cells will also be distributed at random within the parent population and we can consider the statistics of these separately. The essential feature of Poisson distributions is that if N events are observed the standard deviation (SD) associated with that count is square root of N . The coefficient of variation (CV) is then given by

CV = 100 X SD/ N or 100 / sqrt N.

This has two important consequences for determining how much data to collect. If a sub-set smaller by a factor of S is investigated the total number of events processed must be increased by a factor S to maintain the same precision. To improve precision by a factor P the number of rare events recorded, and hence the total number of analysed, must be increased by a factor of P2.

Consider a data set collected for 10000 cells, if a sub-population exists at the 10% level 1,000 of these would be observed with an associated CV of 3.16%, which would be acceptable for many experiments. However, at the 1% level only 100 cells would be expected with a CV of 10% and a drop in precision. This can only be improved by counting more cells and it is useful to construct a reference chart for estimating how many events to process for a required precision.

For a CV of (%) 1.0 2.5 5.0 10 20
Positives required 10,000 1,600 400 100 25
At a frequency of
% 1 in
10 10 100,000 16,000 4,000 1,000 250
1 100 1000,000 160,000 40,000 10,000 2,500
.1 1,000 10,000,000 1,600,000 400,000 100,000 25,000
.01 10,000 10,0,000,000 16,000,000 4,000,000 1,000,000 250,000
.001 100,000 1000,000,000 160,000,000 40,000,000 10,000,000 2,500,000

The table presents such a chart, a total count of 10 7 events which represents about 20 minutes per sample at 10,000 events per second. It is limited to a frequency of 1 in 100,000 beyond which only rough estimates can be obtained even after collecting 10 7 events. Naturally, the sub-set has to be well resolved if these theoretical levels are to be approached in which case the rule is: the number of rare cells examined determines accuracy.

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Golden Rules For Cell Sorting

The intended audience for most of these “rules” is the universal flow cytometry core facility staff member. They were developed for training and educational purposes over the last 10 years. However, in order for everyone’s expectations to be met within the University of Utah core, I believe this list is applicable for both core facility staff as well as the client.

Be absolutely ready at scheduled appointment time, not 5 minutes late, not 2 minutes late
-Clients will notice that it’s not that important to be on time if you’re not ready on time
-Instrument calibrated, cleaned, rinsed
-Experiment opened and ready
-Correct parameters selected
-Relevant display plots opened

It’s all about the sample!!! And it’s all about yield
-Save the bare minimum number of events to allow you to draw appropriate gates for sorting.
-Once gates are set, save more events if needed while sorting
-If you’re running a few samples that will be using the same gates (ex. GFP), start sorting the second you realize that the sample looks good, then save the file.

For complex sorts, never assume you’re done once you started sorting.
-While sorting, spend 10 minutes looking through alternate display plots making sure you have the best possible gating scheme.
Ask yourself:
-Did minor compensation issues cause cells of interest to be partially lost through the gating scheme?
-Is your light scatter gate too small or too large? i.e. missing activated cells or incorporating aggregates?
-Are your live cells slowly creeping up in the dead-cell channel? (or something like that – where live cells slowly get brighter in the PI channel even though they’re still alive)

Being the client’s friend and striking good conversation is a distant second to completing the sort with the highest possible quality
Problems that result from not paying attention:
-Running tubes dry leads to bubble introduction into flow cell, which leads to bad purity and delays
-Forgetting to save a data file
-Forgetting to start sorting
-Time delay results in poor viability and delayed scheduled appointments downstream
-Inappropriate conversation causes people to avoid your lab
-Let’s face it, kids these days can’t handle thoughts longer than twitter length
anyway 🙂

Work with the client to fully appreciate the biology of the experiment!
-A firm understanding of the instrumentation is a small component of what you can contribute to a project

Sometimes the client is right, sometimes you are.
-Work together and be humble. There is always the chance you are wrong
-Often times the investigator is sorting based on another publication with incomplete information.
Example A. Client is trying to reproduce publication stating an antigen to be negative on a cell when its actually dim positive, but less bright than it is on another cell population. This is crucial biological information that can impact how gates and plots are set up.
Example B. The nomenclature and immunophenotype of many common cells are far from standardized. Think Monocyte subsets and Dendritic cells. What you may be familiar with as a specific immunophenotype may not be accepted by another group.

Maximizing available instrument time.
-If you know you’re going to get done with the current sort early, call the next person to see if they can come in early.

I see no need to ever draw a sorting gate based on a histogram

Rarely is a rectangular gate the ideal choice.
-When is the last time you saw a rectangular population?

Filter sample right before you sort, not an hour before back in your lab.

Use appropriate FMO control for dim antigen gate setting

Never sort cells into an empty tube

Never be 100% sure
-We have a tendency to apply something that we ‘know’ from one model system to another, to our own downfall.

Work to foster a warm collaborative environment within the lab

Always have client confirm gates

Follow-up with client about previous sorts
-Make sure they have access to the raw data files, as well as a printout (PDF) of the actual sort gates and post sort purity check.
-If available, a printout (PDF) of the sort report is helpful.  How many cells were processed?  How many cells were sorted?  Calculated efficiency? Final Purity? Final Viability? Final Cell Count?

Develop a simultaneous purity check and cell count protocol
-Over and over you will have to answer the question of “where did all the cells go?” If you do a purity check with Accucount beads, you will know exactly how many cells they walked out of your lab with.

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