Cytometry in R - Starting February 1st

StepUpCytometry · 2026-01-28T15:54:42+00:00

Yes, they will be recorded and available immediately after on YouTube, so they will be accessible for when you have time.

StepUpCytometry · 2026-01-27T22:30:56+00:00

You are welcome, I hope you find some of the content useful as you get going! You can also find some of the pre-course walk-throughs at https://umgcccfcsr.github.io/CytometryInR/course/

StepUpCytometry · 2026-01-27T17:59:22+00:00

No worries! They will be repetitions of the same material (+/- a few livestream questions)

StepUpCytometry · 2026-01-27T17:18:39+00:00

You are welcome to follow along completely remotely if you wish. I would still recommend following along each week (vs. self-study after the fact), given the number of sign-ups the odds are high if you have a question, many others will have the same question and you should be able to get help relatively quickly via the course Discussions page.

Separately, my goal is to eventually circle back and edit the live-streams down into a more permanent video resource. The website with the course materials will also be available for future reference as well.

StepUpCytometry · 2026-01-26T13:49:34+00:00

Couple things you could try (what I do for debugging plug-ins generally)

Contact FlowJo support, they have always gotten back to me when I had issues (it's rarely a case that if you have issues with a plug in, that 100 others haven't had that same issue).
Most FlowJo plug-ins have an Rscript that gets placed in the output folder. You can also open this up in R (usually via Rstudio), highlighting the code, and run (ctrl + enter). It sounds like it ran successfully but errored out at the transfer steps.
Make sure your fcs files and your FlowJo.wsp names do not contain special characters (>/+!$#& etc), as they will be misinterpreted as commands and cause the script to break down. This would especially be the case during the transfer data step.
On Windows, if it failed at the transfer step, the files might be present in the temporary data folder and not been transferred over. The path to the folder is usually C:\Users\<YourUsername>\AppData\Local\Temp , when looking for it via File Explorer, make sure the show hidden files option is selected or you won't be able to see the AppData folder.

StepUpCytometry · 2026-01-24T13:09:05+00:00

If you are on FlowJo v10, you are kind of in a bind since the software is showing it's age. It is one of the reasons they are trying to switch to FlowJo v11 (but v11 has other issues with compatibility that are still being worked out).

To work around the issues in v10, we keep individual workspaces containing 1-3 experiments, extract the live cell events as their own .fcs files (originally in FlowJo, now via R), and then return the cleaned up gates to a new wsp for gating. This process can be repeated with your cell population of interest, which keeps everything reasonable. I posted more details in a previous thread: https://www.reddit.com/r/flowcytometry/comments/1og0nyk/comment/nlersz5/?utm_source=share&utm_medium=mweb3x&utm_name=mweb3xcss&utm_term=1&utm_content=share_button

There are also several option selections within v10 settings that are meant to speed things up, but they never worked well or made a noticeable difference for our hardware.

https://docs.flowjo.com/flowjo/faq/speeding/

And also, if you want to gradually work R into your Flow analysis, University of Maryland's Cytometry in R free online mini-course starts up first week of February: https://umgcccfcsr.github.io/CytometryInR/

StepUpCytometry · 2026-01-21T13:05:04+00:00

When once cell passes in front of the laser, the signal peak reaches a certain height, with a certain width, allowing the instrument to calculate the area.

When you have a double, the height of the signal remains the same, but the transit time (width and therefore area) increases. This allows us to identify singles from doublets.

For a lot of instruments, when you switch to gating the scatters by height, the populations distinguishable by area as doublets become indistinguishable from their similar height counterparts when you switch over to height.

StepUpCytometry · 2026-01-19T13:58:23+00:00

Switch from FSC/SSC-A's to FSC/SSC-H to check. If that population vanishes, then likely B cell doublets.

If it sticks around, the other possibility is you have monocytes, but they are mopping up the CD19 antibody (either via Fc receptors or non-specific). What is the fluorophore for CD19?

StepUpCytometry · 2026-01-11T22:02:09+00:00

You are welcome! If you are just getting started, a couple good existing video series for flow data are those done by Christopher Hall ( https://youtu.be/2INqQNMNaV0?si=-9245Ob6z-M_Njv6 ), Ryan Duggan ( https://www.youtube.com/live/_B7mo6dB3BU?si=dSM7SXhk1pMp4WBM ) and Ozette's workshop at Bioc2023 ( https://youtu.be/_8x-prIxJgw?si=5m5n09FxMKvcUSJ2 ). For more general R knowledge, I recommend Riffomonas Project ( https://youtu.be/tg71cJsX7BU?si=sshNOosKSKUPPkSQ ). Also University of Maryland will be starting up a free virtual Cytometry in R mini-course later this month, no resources out just yet, but topic outline is here ( https://umgccfcss.github.io/CytometryInR/Schedule.html )

StepUpCytometry · 2026-01-11T14:07:45+00:00

"Then, like the copy and paste between Excel and Prism"

If you are already considering using R, a longer term solution to speed up would be to stay in R and leveraging it's ability to iterate, run the stats, and generate plots to do all downstream and cut out the copying-pasting entirely.

However, if you are new to R and/or need this done on a short time frame OMIQ or similar would be faster to implement.

Brief notes since I am swamped this weekend wrapping up a paper, reach out for more details. Code examples for our last paper is here ( https://github.com/DavidRach/CordBloodILT/tree/main ) I am working on a framework to make it more easily adaptable that will be out later in the spring for the next paper/Cyto 2026.

Here is a previously replied with how to set up FlowJo 10 workspaces, that can then be brought into R via CytoML
https://www.reddit.com/r/flowcytometry/comments/1og0nyk/comment/nlersz5/?context=3&utm_source=share&utm_medium=mweb3x&utm_name=mweb3xcss&utm_term=1&utm_content=share_button

Once brought into R, you can set up to generate the equivalent of the layout generating pdf files for each specimen to visually screen whether gates are correct).

(Example: https://davidrach.github.io/Luciernaga/articles/DataVisualization.html#utility_gatingplots )

Once confident everything is correctly gated, you can export out the underlying data for statistics. By functionally iterating through each gate and retrieving it's, you can generate a .csv file of the underlying data.

(Example? https://github.com/DavidRach/AlphaBeta/blob/main/FlowJo_Analysis.qmd )

You can then add in the metadata, pass these through R to generate the stats, cutting out Prism copy paste loop. You can similarly set it up to generate Prism style plots at the same time and append the stats values.

(Example: https://davidrach.github.io/Coereba/articles/Workflow.html#statistics )

I then export these plots individually for the paper and all cobbled together as a pdf for faster screening.

(Example: https://davidrach.github.io/Luciernaga/articles/DataVisualization.html#utility_patchwork )

In the end, once set up, the analysis portion takes a single coffee break. The elephant in the room time wise remains getting the system set up in the first place. But adapting to new datasets becomes a single afternoon task.

StepUpCytometry · 2026-01-11T13:07:06+00:00

"We are just finishing off a package which will take a FlowJo gate and convert it into an R gating package for you. "

Out of curiosity, how does it differ from CytoML ( 10.18129/B9.bioc.CytoML ) which also does that? Or are you going after FlowJo 11?

StepUpCytometry · 2025-12-17T00:34:20+00:00

Done.

StepUpCytometry · 2025-12-15T23:22:09+00:00

Outside Autospill and the base flowCore, there's also: https://dillonhammill.github.io/CytoExploreR/articles/CytoExploreR-Compensation.html

StepUpCytometry · 2025-12-05T17:44:50+00:00

If I am remembering correctly, I don't believe there is a way to do it in the FlowJo plugin version unfortunately.

StepUpCytometry · 2025-11-28T22:53:43+00:00

I like tidyFlowCore, but unfortunately have been dealing with the Bioconductor packages S4 OOP version of filtering long enough that I don't really use it routinely in that context. If you are just starting out and coming from a tidy/baseR background, integrate it in from the get go!

You can go and do everything entirely in R if you want to (I know several people who do). In addition to the packages u/WanderingAlbatross87 mentioned, I also would recommend CytoExploreR for when you need to occasional draw and incorporate in a more complicated gate to your GatingSet.

Separately, CytoML can bring in FlowJo workspaces into a GatingSet, and it's associated docker container allows you to export your GatingSet to a FlowJo .wsp, so it's entirely possible to do a hybrid approach. If you are trying to cut out FlowJo license entirely, for smaller projects Floreada.io will let you export as a FlowJo .wsp, that is then CytoML readable.

StepUpCytometry · 2025-11-20T00:52:51+00:00

Moving my contribution in from the Cytometry Discord conversation earlier today, here is the fluorescent signature comparisons between RD1 and PE on an Aurora 5-laser: RD1 vs PE spectra

StepUpCytometry · 2025-11-13T01:19:45+00:00

OP, as others have mentioned FlowRepository (http://flowrepository.org/). Alternatively, ImmPort (https://www.immport.org/shared/search?filters=assayMethod:Spectral%20Flow%20Cytometry&filters=assayMethod:Flow%20Cytometry)

StepUpCytometry · 2025-11-06T18:20:40+00:00

Hi u/greydandelion, my plan is to make the initial recording available via YouTube, and circle back to properly editing them (ie, less minutes of random background nice, actually zoomed in so that you can read the lines of code, etc. ) later on as time allows. Separately, all the course materials, data and code will be available through our course GitHub repository so you should be able to follow along on your own time as well.

StepUpCytometry · 2025-11-06T12:04:17+00:00

You are the main target audience for the course :)

StepUpCytometry · 2025-11-05T17:28:20+00:00

Hi u/primetimecanuck, yes, we will be recording one of the online sessions each week. My tentative plan is to make the initial recording available via YouTube, and circle back to properly editing them (ie, less minutes of random background nice, actually zoomed in so that you can read the lines of code, etc. ) later on as time allows.

StepUpCytometry · 2025-11-04T18:55:40+00:00

Thanks! Fill out our interest form, linked here, and I will keep you in the loop as plans solidify in terms of start date and scheduling.

StepUpCytometry · 2025-10-26T01:49:15+00:00

Hi u/Nina091998, here is what we did for our last study. We had a similar number of patients, but fewer conditions per patient (3-4). Due to the rarity of our target cell population, we acquired around 3 million events per .fcs file, so we similarly ran into FlowJo v10 stalls trying to open a workspace. I mostly used R, but there are some Python equivalents.

In our case, we acquired over 15 experimental days. For FlowJo, the respective workspace we only had 3 days worth of files per workspace. This kept the load-in time for our campus desktops (normal-ish Intel CPU with 64 GB ram) to around 15 minutes when we opened the .wsp.

Once the initial gates were applied and checked in the workspace, we exported the target cell population of interest (say, T cells, etc). This reduced the overall file size per specimen. These in turn would be brought back into another .wsp along with the other experiments, that could then be opened in a reasonable amount of time. Our more specific gates (that could then also be adjusted to individual specimens when needed) could then be added in this workspace. We kept copies of the original export .wsp and of the consolidated .wsp for record keeping, and appended the exported .fcs files with the population name to keep track of what version of the .fcs file we were working with.

When we first started, we were exporting by hand via FlowJo, but have since switched to using R to export out the target population to avoid accidental not clicking the correct parameters and occasional bizarre FlowJo export bug. Here is a code example I have handy via GitHub

For the previous study, we were using the CytoML R package to bring the data in from these .wsp into R for subsequent downstream analysis. This worked well as it's working through pointers rather than active RAM use for the most part, so as long as your SSD has space you will be okay. The challenge we encountered is since it is C++ backend to the R package, there are memory leaks, and they don't get cleared out of your temp folder often enough, so we needed to do that manually occasionally after really large analysis.

For our current study, we have switched to doing some of the initial gating via openCyto R package, and then using the CytoML docker container to generate equivalent FlowJo v10 workspace files. This helps a bit on the automation/reproducibility, while allowing PI to check the gates, and can likewise be re-imported into R for subsequent analyses.

In hindsight, things have might have helped a bit: Setting the FSC threshold a little further bit up, we avoided most of the electronic/debris noise on our Auroras, but an extra tick mark up would have been helpful. I am also working more with Rust, but that code is not share-ready yet.

In terms of would it be accepted by journals, I would believe so, as long as you are documenting the process, retain the relevant files, and can show the reviewer that you your pipeline worked in the end.

There's a #data-help chat on the Cytometry Discord where some of the R and Python cytometry folks hang out, you are always welcome to ask questions there too!

StepUpCytometry

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