[3dem] [ccpem] Adequate particle normalization prior to 2D classification?

Sun Jan 31 13:18:55 PST 2016

Well, since *I'm* the guilty "people" (and apparently have company), I thought I should say that it was a casual error and that I'd no reason to think Schors wouldn't know exactly what I meant. Apologies for my unfamiliarity mostly to Scientific Reports. Glad we're keeping pretentiousness in check. And that ya'll are having this debate on Sunday. ;-) But thanks in all sincerity for the dialogue - I stand corrected!

Very best,
Nancy

Sent from my iPhone

On Jan 31, 2016, at 8:35 AM, Edward Egelman <egelman at virginia.edu<mailto:egelman at virginia.edu>> wrote:

    Why are people using "Nature, Scientific Reports"? The journal's name is Scientific Reports, and Nature is the publisher. By this logic I could say that I was the Editor-in-Chief of Cell, Biophysical Journal, since Cell is the publisher of BJ. Not to rain on Marin's parade, but If one looks at Peer Review Policy for Nature publications, it states:
"The policy outlined on this page applies to Nature journals (those with the word "Nature" in their title). NPG publishes many other journals, each of which has separate publication policies described on its website."
The policy for Nature journals goes on to explain the need for novelty, significance and likely impact.  In stark contrast, this is what they say about Scientific Reports:
"To be considered for publication in Scientific Reports, a paper must be technically sound original research, without any requirement for impact or a conceptual advance."
  Just my two cents (which are worth less and less).
Ed

On 1/30/16 8:07 AM, Marin van Heel wrote:

Dear Nancy,
What Sjors is suggesting is a simplified version of what we suggested in:
"A posteriori correction of camera characteristics from large image data sets", P. Afanasyev et al, Nature, Scientific Reports.
The camera correction should preferably include the subtraction of the average background and the normalization of the standard deviations of the pixel vectors, especially if you are operating your DE camera in integrating mode. The movie alignments can improve significantly after the a posteriori camera correction.  The other aspect is the FRC validation of the camera correction. The FRC is then not used as a ‘gold standard’ 2D resolution criterion but rather as an indicator of the independence of different images collected with the same sensor. The FRC should not cross the 3-sigma threshold indicating the expected random noise fluctuations around FRC=0. For details see the paper.
If you want to test the a posteriori camera correction programs, contact <mailto:michael at imagescience.de> michael at imagescience.de<mailto:michael at imagescience.de>!
Hope this helps!
Marin

=====================================

On 28/01/2016 00:48, Nancy Meyer wrote:

Again, thank you for the reassuring response! Maybe I've lucked out with similar image intensities in previous datasets - I should probably look at a few min/max, mean, and stdev values to convince myself.

I was pretty careful to remove particles on that horiz artefact and if restoring their inclusion is the biggest gain from redoing gain correction, I can maybe let that slide for now. I did just see "A posteriori correction of camera
characteristics from large image data sets", P. Afanasyev et al, Nature, Scientific Reports, after looking up your recommendation - looks like they've implemented it in Imagic  - wonder if you could do the same correction in just ImageJ...

Thank you for taking the time to look at the images... slowly getting the hang of Relion, but the input is so invaluable!

Best,
Nancy

______________________________________
From: Sjors Scheres [scheres at mrc-lmb.cam.ac.uk<mailto:scheres at mrc-lmb.cam.ac.uk>]
Sent: Wednesday, January 27, 2016 1:10 PM
To: Nancy Meyer
Cc: ccpem at jiscmail.ac.uk<mailto:ccpem at jiscmail.ac.uk>
Subject: Re: [ccpem] Adequate particle normalization prior to 2D classification?

Hi Nancy,
The particles look perfectly fine to me. The overall differences in
greyscale you see is because each of the particles is scaled from white to
black with their own min and max values, which are susceptible to
outliers. The mean will probably be perfectly fine. You can get rid of
this with removing white and black dust, but it will not be necessary to
do so.

The classes also look quite OK. Just select all the nice ones and proceed
with another 2D classification or go into 3D already. Some details are
already coming up, so the 3D structure will look nice.

The micrographs show a sign of a bad gain correction. If you have many of
them (> several hundreds) you could correct the gain a-posteriori by
calculating the average of all micrographs and then divide each micrograph
by that average. This should get rid of the horizontal artefact (as long
as it is present in all micrographs). That may save some particles that
lie on that line.

HTH,
Sjors

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