[Cytometry] Scaling problem with FACSDiva

Cris Bare flowmail at verizon.net
Thu Feb 6 04:40:11 EST 2014


Well, Mario beat me to the reply, with his usual eloquence.

I will add an example, though.

Not too long ago I was teaching a colleague titrations using a FACSCanto
II. Samples were single color and display plots were univariate histograms.
DiVa did a decent job of Biex transform and during acquisition I had clear
positive and negative peaks.

When I brought the data into both Flowjo vX, and FCSExpress 4, the
histograms suddenly displayed bizarre triple peak negative populations, and
automatic scaling pushed them clearly into negative number space despite
having zeros for the compensation matrix. I could reproduce the acquisition
histograms by manually adjusting width basis (Flowjo) and log/lin
transition points (FCSE). It seemed there was quite a lot of baseline
restoring in this data, which I suspect was due to the cleanliness of both
samples and system.

Regardless of how odd the histograms looked, when the stain index was
calculated, the teaching point of the titration became clear. I wouldn't
use those plots in any presentation, but the underlaying data said exactly
what I wanted to hear.

-cbb


On Wed, Feb 5, 2014 at 6:28 PM, Mario Roederer <roederer at drmr.com> wrote:

> Dave Dunaway wrote:
>
> > I find this to be dubious advice unless all you are interested in is
> crunching numbers.
>
> But, in fact, that's ALL we should be interested in.  Graphs are for
> illustration purposes, for data exploration purposes, and for pretty
> pictures.  We should not draw conclusions from graphs, we can only do so
> from numbers, properly controlled, properly analyzed, but numbers
> nonetheless.
>
> and,
>
> > The data may be there but if its not visibly demonstrative then your
> data is questionable when it comes to presentation.
>
> "Visibly demonstrative"?  I'm not even sure what you mean by this.  But it
> illustrates a basic mistake we all make -- we put too much emphasis on
> visualizations, on graphs.  Data is questionable based on evaluations of
> its reliability and reproducibility (statistics).  We can look at graphs to
> decide on what questions to ask of the data, but we must be cautious about
> drawing conclusions from graphs.
>
> I can show you examples of graphs which look great but are meaningless.
>  And I can show you graphs of data that look questionable but are good.
>
> Cris's basic advice was correct, but brief.  If your positives are within
> a half decade of the top end of the dynamic range, then reduce your PMT
> voltage (sensitivity).  Inserting an ND filter is not necessarily an
> equivalent (or good) solution -- it accomplishes roughly the same thing but
> at a cost of increased noise from decreased photoelectron counts.
>
> Reducing the PMT voltage won't make negatives "invisible" -- it will only
> squash them near the zero value.  Nothing is hidden.
>
> BTW, when you see your negative population go in to the "below-zero"
> measurement range of uncompensated parameters (ie towards the left edge on
> the transformed logicle scale), this is a consequence of the baseline
> restore in the DIVa electronics.  It's a pain... but it's not typically a
> problem.
>
> Just make sure that you consider ALL events below the upper end of an
> unstained sample (wherever it ends up on your settings) to be equivalent.
>  i.e., if your unstained cells go to 100, then EVERYTHING below 100,
> whether it's +10 or -300 is the same -- don't gate separately those events,
> even if they look like distinct populations in your graph.
>
> Because graphics can lie, but numbers always tell the truth.
>
> mr
>
>
>
>
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