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Minimum number events in gate for downstream analysis?

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KatieVowell

Participant

Posts: 1

Joined: Fri Sep 14, 2018 2:12 pm

Location: Upper Providence, PA

Post Fri Sep 17, 2021 1:55 pm

Minimum number events in gate for downstream analysis?

Hi! I'm analyzing a large CyTOF data set from DTC samples and the cell #'s in some donors is quite low and I'm wondering if other folks use a minimum event # in a gate to continue/report downstream analysis (% marker+ or MMI)? A few years ago, we performed an experiment in house with replicates and worked with statisticians to determine the minimum # of events needed, and below 100 events the CV's started to increase significantly. So we made the cutoff at 100, meaning if you have 400 T cells and you gate for Tregs and there are 10 events, you can report 2.5% Tregs (out of CD4), but would you would not report downstream gating off of the 10 events (e.g. % activated Tregs (out of Tregs), or MMI of CD39 on Tregs). Does that make sense?

I'd like to drop this to ~20-40 events for this data set but wasn't sure what we'd hear from reviewers if we made this cutoff. Anyone have any advice/thoughts?
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mleipold

Guru

Posts: 5796

Joined: Fri Nov 01, 2013 5:30 pm

Location: Stanford HIMC, CA, USA

Post Fri Sep 17, 2021 5:10 pm

Re: Minimum number events in gate for downstream analysis?

Hi Katie,

In your post, you say that historically you've used Pop X Count to set a denominator threshold for a Freq calculation (eg, you're OK with reporting a number for PopX/Parent but not Child/PopX when PopX Count is low). You've historically set the threshold at Count=100, and you're wondering if you can set it lower (Count=20-40).

I think this is partly related to a recent thread on cell acquisition/number here: viewtopic.php?f=1&t=2670

In it, Cynthia Guidos does a good job discussing things like CV thresholds and therefore cell number needed. In particular, "Lower precision (10-20%) is generally acceptable for rare event analysis when it is not feasible to collect enough events to achieve higher precision."

There's also this article ( "Technical issues: flow cytometry and rare event analysis" PMID: 23590661 ) which discusses this in Table 1. I think you need to talk with your statisticians and decide on the lowest threshold (CV) that you're going to allow. Looking into statistical decisions made on RNAseq data might be a good thing too: in almost every case (cost, etc), they are dealing with far fewer cells than you would ever have in a cytometry experiment.


I guess there's a second question with regard to your MMI question: are you also looking for a separate confidence threshold for the Metal Intensity value you report, or are you simply asking what Freq CV threshold you'd need in order to report *any* MMI value? With Freq CV, you're talking about the confidence of robustly detecting and properly quantifying the *presence* of something. With Metal CV, you're talking about the confidence of assigning a signal intensity value. If you think about this in the realm of a highly uniform sample like beads, it would be the difference between spiking the beads in at different concentrations (Freq CV), versus the signal intensity distribution of the metal signal in the detected beads (Metal CV).

Formally, I'm not sure that the Freq CV would scale at exactly the same rate as the Metal CV: in the bead example, the signal intensity on the beads is highly uniform (tighter distribution), so I would think that you would need fewer events for a given SD/CV threshold for the Metal Intensity. In the case of a cell sample, though, I would assume that biological variability (broader distribution) would lead to a greater Metal Intensity variability. This would depend on the marker in question: for example, CD27 is fairly tightly bimodal on T cells with a small MMI distribution in both CD27pos and CD27neg populations, whereas CD38 expression is much more smeary (broader distribution).


Mike

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