Dear Mario, flow world, A justifiably aggressive response - as one would expect from a real flow genius who sees things needing correction. Like many others, I tune into most items you post on this list with great interest. You've got a great delivery, your stuff is well structured - a knack for taking this complicated 'stuff' and clarifying it. We all owe you! I've been a fan since day 1. Thank you for the clarification on slight shifting by one of two populations having similar but not identical autofluorescence characteristics. I knew that but should have disclaimer'd my comments. Thank you for the piece on histogram and bivariate representation of data. You've got me on the math 'stuff' there; I just follow that the GFP analysis I've done is a bit more accurate using bivariates, and histograms won't show you the diagonal effect of autofluorescence that bivariates will. I should have mentioned that we should at least view data on a bivariates before going to the histogram - just to be sure. I always do - I hope this proves to have been good practice. I've read your postings on isotypes and agree with you that they are, well, challenging. Yes, I'm still working to get to Jedi level - but my intentions in responding as I did were good, as are my intentions with FlowJock.com to help out people with getting up and running. Nothing will substitute for the sheer wealth of info available through Mr. Shapiro, or you, or Herzenberg or Loken or all the other flow legends out there. I can't believe nobody has started a trading card business for you folks yet (could be a hit at ISAC). >From what I've seen, however, most of the flow users out there turn on the machine, calibrate, run samples, drop a quadrant or a marker - and print the stats. It would be great if we could get them all to read all the Purdue posts, or if everyone knew what it required to get good stuff out of 12-color data. As the flow guy at various shops out west, I've seen the amount of instruction needed by the rookie contingency. That's where businesses like FloCyte Associates (from the great things I've heard) and FlowJock.com come in. FlowJock.com has some nutshell overviews of what a flow cytometer does (not in MR terms, but in Average Joe terms). It's just a dusting, really. The economic engine of the business is fueled via the marketing of quality, narrated, screen-capture videos showing the basics: 1) What does it do to a population of beads when you adjust PMTs and amp gains? This, of course, is the basics of instrument optimization. 2) What do you need to do differently on a FACSCalibur to optimize for cell cycle? I show the whole optimization process, including why you need the DDM, why FL2 needs to be in Linear, etc. 3) How can you get cell cycle stats using ModFit's Sync Wizard? 4) What does it look like to change a nozzle on a MoFlo and de-bubble - and then optimize? How do you name a parameter in Summit? 5) How do you do three-colors plus PI on an FC500? 6) How can the tools in FCS Express make my life easier? 7) Etc. Sure, we talk about this stuff here at Purdue and on core websites globally, but why not have a narrated video showing a rookie what it looks like? I know I could have used these babies when I first encountered cell cycle optimization at UCLA. The videos show our current instruments and software products in action. I might add that they show the ease with which these instruments can be operated. This will not only settle a nervous rookie, but it'll show the customers how easy it is to use the instrument or program. Why the manufactures aren't already doing this in big ways I'll never know. Anyway, FlowJock shows basic stuff - nothing approaching the level in which big-time flowjocks like you operate, but really quite useful for those who think that such material is useful and that leaving a 6-color rare-event sort to answer rookies' PMT questions is a bit tiresome. Just give them the FlowJock CD. As far as the rest of the stuff you said regarding expectations about my videos and the premature self-assigning of the FlowJock moniker, I'll just forget about it. The perceived personalities of frequent Purdue contributors maintained by the majority of subscribers won't be affected by your valuable criticism of my comments to Ms. Dahl, and the biz is too small to hold a grudge! You should have responded the way you did - you did the right thing to clarify my wrong statements. But I was surprised by the overall flavor of it. In this gig it makes sense to put it this way: expertise, like MFI measurements, is relative. If I'm in the second decade, you're certainly in the fourth or fifth. If only I could get to you by cranking the PMT settings! Still, I like to post to the list, and I hope to learn more from you upperclassmen. Regarding the FlowJock trademark...I would have taken FlowMaster, but some darn muffler company already had it. I registered FlowJock so it wouldn't get nabbed by a carburetor or irrigation company. You and everyone will hopefully call yourselves FlowJocks as much as you like. I'm not taking advantage of anyone's good will, and if you want to challenge the trademark and work on taking it away, I'm okay with that (this isn't about me proving myself right or hanging onto the name, I just didn't want it to be taken by a non-flow organization). Thanks again for the knowledge, Dr. Roederer, and I hope this finds you and everyone else superb and clog-free. I apologize for contributing to the forum inaccurate information, and I will work on improving upon that! My sincere apologies go to Christine Dahl, to whom I first replied on this subject. Sincerely, Nate Nate Regimbal FlowJock Where even Michael Flatley's clogs are considered un-cool. _____ From: Mario Roederer [mailto:roederer@drmr.com] Sent: Tuesday, September 14, 2004 6:06 PM To: cyto-inbox Subject: MFI vs %Positive: myths deserve answers In response to a recent posting by a self-trademarked FlowJock: There's been extensive rigorous analysis of %Positive quantitation with dim populations--look it up in the literature, there are a number of papers (see bottom of email). Many third party software programs support these types of analyses; for example, FlowJo can compare the negative and stained controls using the five somewhat-related algorithms devised by Roy Overton, Bruce Bagewell ("SED"), Cox (Cox chi-square), Kolmogorov and Smirnoff ("K-S"), as well as by our own group ("PB" or probability binning). In general, these algorithms agree quite well--although the Cox, KS and PB methods aren't strictly %Positive quantifiers (but can be adapted to be such). In my opinion, for %Positive, the best is the SED algorithm. This has significant support both from basic mathematical principles as well as from empirical analyses. The PB method has the unique facet that it can be used to "gate" on cells that are different (e.g., positive) in one or more dimensions. Now let's dispense with a few myths that you brought up! ... When the whole peak shifts, the whole population is brighter than the Negative control population. That means it's 100% positive - including those dim cells in the 'positive' peak that aren't as bright as the bright cells in the negative peak. That's not really true, for a number of reasons. First, you haven't defined what you mean by "peak". If you mean the "mode" (which is what most people mean when they think of peaks), then it's not at all true; the mode can be significantly influenced by changes in underlying representations of positive and negative; an increase in the mode does not mean that the cells are 100% positive. Even if the "whole peak" (by which I assume you mean the bottom percentile as well as the top percentile) moves, this does not indicate that all the cells are positive! Consider the simple example of an unstained population that is actually comprised of two sets of cells: A & B, where "B" cells have slightly more autofluorescence than "A", but the mixture doesn't resolve and appears to be a single peak. After staining, all of the "A" cells become slightly positive, and are slightly brighter than the B cells, which are still negative. Again, the distribution doesn't resolve into 2 peaks. That's a simple case where half of the population is staining, yet "the whole peak shifts"! Is this a trivial example? Certainly not: Within lymphocytes, B cells and T cells have different autofluorescence levels--so if you were to stain one population only with a dim reagent, you might mistakenly conclude that all of the lymphocytes express that antigen! Back to the 'small differences' case: If your negative control is in one location, and the negative cells in the test sample are in the same location but there are a few bright cells, then you can use frequency analysis to get the percentage of those positive cells (use a 2-parameter plot and a polygon region - NEVER a histogram). Well, that's a blanket statement that I must also disagree with! Why "NEVER" use a histogram? Admittedly, I use bivariate plots often to gate essentially one a one dimensional expression. But I do so with guilty pleasure. The claim appears to be that you can better separate the dim positives from the negatives on a bivariate display. And this is visually supported in many cases. However, this is purely a visual artifact! It's magic! It's not mathematically true! In fact it's.... myth! EXCEPT when there is a relationship between the expression of the dim marker and the measurement on the other axis (and there often is--particularly with something like SS or FS, when there is a size-dependence). If that's the case, then you can't use just any bivariate display, you must use the bivariate display of your interesting marker against the parameter which provides additional information. If the other parameter in the bivariate display is not mathematically related to the measurement marker, then there is no scientific basis for stating that the resolution of the dim cells (ability to gate) is better in a bivariate display. And yes, I'd be happy to follow this up with real math if necessary. One thing to consider is that dot plots are heavily influenced by the number of events you collect. Pretend that you had collected a trillion events instead of 10,000 -- all of a sudden, the distinction on that bivariate plot has disappeared! (And yet, the histogram looks no different). Furthermore, the assertion that gating on bivariate plots is better than on histograms belies the underlying assumption that the gating is completely subjective! Don't be misled by the typical elliptical (or circular) distribution of events in a bivariate display of uncorrelated parameters -- this does not help you identify boundaries any better than from a histogram, except in a subjective manner. Of course, there's nothing wrong with subjectively placing gates, as long as you are aware that this is the case. But if your are concerned about accurately estimating %Positive, then certainly any subjectivity in gate placement must be removed. Incidentally, the algorithms referenced above do an excellent job of estimating %Positive, whether the expression is bright OR dim. Manual gating fails miserably if there's no defined separation. If you have brighter events AND your negative peak moves up, you either have 100% positivity in your sample (with 'dims' and 'brights') OR your negative control isn't working properly and you only have a few bright positive events. OR... your negative control works just fine, it's just that the stain has some nonspecific binding on the nonexpressing cells! Oh wait -- this means your negative control isn't an adequate control... but then, that's almost always true. It's nearly impossible to have the perfect negative control. (And please, don't even get me started on isotype "controls" -- something I want to rename as "isotype uncontrols"). Nonetheless, the point is that there are lots more possibilities than the two you mention. PS-The training videos will be available in October. Well, great! ... but I hope they carry a bit more rigorous explanations than your original response... Perhaps the self-assignment of the moniker "FlowJock" is a bit premature. (PS, I sincerely hope you don't try to claim a trademark on a term that has been in general use by the community for many years--that would be a waste of effort and community good will). mr (you may consider me as an untrademarked FlowJock) 1) Overton WR. Modified histogram subtraction technique for analysis of flow cytometry data. Cytometry. 1988 Nov;9(6):619-26. 3) Roederer M, Treister A, Moore W, Herzenberg LA. Probability binning comparison: A metric for quantitating univariate distribution differences. Cytometry. 2001 Sep 1;45(1):37-46. 4) Roederer M, Moore W, Treister A, Hardy RR, Herzenberg LA. Probability binning comparison: a metric for quantitating multivariate distribution differences. Cytometry. 2001 Sep 1;45(1):47-55. 5) Roederer M, Hardy RR. Frequency difference gating: A multivariate method for identifying subsets that differ between samples. Cytometry. 2001 Sep 1;45(1):56-64. 6) Cox C, Reeder JE, Robinson RD, Suppes SB, Wheeless LL. Comparison of frequency distributions in flow cytometry. Cytometry. 1988 Jul;9(4):291-8.Received on Thu Sep 16 16:59:55 2004
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