Dear Charles,
Thanks for the kind words, and thanks for the links to your papers! I hadn’t
run across them before — they look very interesting and relevant, but it will
take a bit of time to digest them!
Randy
> On 9 Oct 2024, at 21:36, Sindelar, Charles <charles.sinde...@yale.edu> wrote:
>
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> ul {margin-bottom:0in;} --> Randy, what a beautiful paper! I love it. I’m
> also a huge fan of the you guys’ resolve_cryo_em density modification paper,
> which had a major impact on my group’s ability to interpret several
> challenging structures.
> Many moons ago when I was a postdoc with Niko Grigorieff, I got interested
> in this problem of Fourier over-sampling and we published a couple papers
> working out the correction factor (particle/volume ratio) and its
> relationship to FSC’s and the Wiener filter.
> https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22613568/
> https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21757012/
> Two of our results I thought were especially fun, and maybe not commonly
> appreciated even now, were
>
> • one can estimate the particle/volume ratio just by doing signal
> analysis on a small interior region of the 3D map
>
> • the ‘ad hoc’ input parameter T of Relion, still required as user input
> in the current version for 3D classification, corresponds to the inverse of
> this correction factor
> Best wishes, Chuck
> From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> on behalf of Randy
> John Read <0000eafc0efa8263-dmarc-requ...@jiscmail.ac.uk>
> Date: Tuesday, October 8, 2024 at 4:07 AM
> To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK>
> Subject: Re: [ccp4bb] Review: Linearity and Resolution in X-Ray
> Crystallography and Electron Microscopy
> Dear Marin,
>
> In crystallography we do have the information gain measure (based on
> Kullback-Leibler divergence) that my group put forward and implemented in our
> Phaser program (https://doi.org/10.1107/s2059798320001588). Signal and noise
> aren’t isotropic, so information gain isn’t isotropic either. However, we’ve
> observed that the resolution at which the average information gain is about
> 1/2 bit per reflection corresponds roughly to the resolution limits suggested
> by other techniques. Given the interpretation of information gain as the
> maximum log-likelihood-gain that one could achieve from an observation with a
> perfect model, it’s a very natural measure to use for the useful resolution.
> I don’t think this measure has gained much traction in the crystallographic
> community yet, but it’s becoming more widely available in some data analysis
> tools.
>
> We’ve used the same KL-divergence approach to estimate the information gain
> from a Fourier term in a cryo-EM reconstruction
> (https://doi.org/10.1107/s2059798323001596). In the implementation of this in
> our EM-placement docking software, we have anisotropic estimates of signal
> and noise, so again the information gain is anisotropic. Somewhat to my
> surprise (given the differences in the derivations), our information gain
> measure turns out to be equivalent to yours
> (https://doi.org/10.48550/arXiv.2009.03223) if we assume that the signal and
> noise are isotropic. As you point out there, for cryo-EM reconstructions it’s
> essential to consider the effect of over-sampling of the Fourier transform
> and the corresponding lack of independence of the Fourier terms, so this has
> an over-sampling correction factor.
>
> Best wishes,
>
> Randy Read
>
> > On 8 Oct 2024, at 00:02, Marin van Heel <marin.vanh...@gmail.com> wrote:
> >
> > Dear Marius Schmidt
> >
> > In my (our) original FRC/FSC papers (1982; 1986 ; 2000; 2004; 2017; 2020;
> > 2024) the linearity of these correlation functions/metrics have been
> > extensively discussed. Historically, EM started at a low resolution
> > "blobology" level whereas X-ray crystallography (XRC) at that time, already
> > had reached atomic resolution. This led to the belief that the XRC
> > resolution metrics ( like phase residuals and R-factors) were also
> > appropriate as resolution metrics for EM. However, in XRC the measurables
> > are diffraction patterns for which amplitudes corresponding phases had to
> > be derived iteratively. In EM and in imagining in general, the measurables
> > are the images themselves, that contain both the amplitude information and
> > the phase information. To revert to the then already established XRC
> > resolution metrics like phase residuals or R-factors, implied discarding
> > the most important part of the available information (see the Why-O-Why ).
> > (https://www.linkedin.com/posts/marin-van-heel-5845b422b_whyowhyarchive-activity-7149738255154946048-Oc93/?utm_source=share&utm_medium=member_desktop).
> > That problem was realized soon and the mentioned FRC and FSC metrics were
> > thus suggested which exploit all the available information. Thus, the XRC
> > atomic resolution technique of the 1980s came with a low-quality resolution
> > metric whereas the Cryo-EM low-resolution blobology approach of the 1980s
> > came with a high-quality resolution metric.
> > Thus, in summary, all resolution criteria in XRC are ad-hoc non-linear
> > metrics that have no general validity outside of XRC. Looking at only the
> > amplitudes of a diffraction pattern is like finding the highest resolution
> > spot in a diffraction pattern, where, even if the spot is clearly visible,
> > that does not mean one would be able to find its phase. We need a more
> > comprehensive metric that has a wide range of applicability. In other
> > words, where a CC1-2 metric cannot be applied to assess the 3D brain scan
> > of a brain-tumor patient, the FRC / FSC, and the newest FRI / FSI metrics
> > can be applied in all cases
> > where 2D and 3D data are dealt with!
> > Hope this helps,
> >
> > Marin van Heel
> >
> > On Mon, Oct 7, 2024 at 3:04 PM Marius Schmidt <smar...@uwm.edu> wrote:
> > I think this is taken care of:
> > The CC1/2 and the CC1/2* are appropriate metrics for the resolution limit.
> > They are all spit out by newer data processing software.
> > The CC1/2 is directly comparable to the FSC. Many people use CC1/2 = 1/e as
> > the resolution limit.
> > In many cases of data the CC1/2 = 1/e is equivalent to I/sigI of 1, which
> > is used sometimes as a metric for the resolution limit (some use I/sigI =
> > 2),
> > and in more cases the CC1/2 corresponds to Rmerge in the range of 40%.
> > For serial crystallography, the R-split goes through the roof at CC1/2 =
> > 1/e,
> > so the CC1/2 is the better metric.
> >
> > Best
> > Marius
> >
> >
> >
> >
> >
> > Marius Schmidt, Dr. rer. Nat. (habil.)
> > Professor
> > University of Wisconsin-Milwaukee
> > Kenwood Interdisciplinary Research Complex
> > Physics Department, Room 3087
> > 3135 North Maryland Avenue
> > Milwaukee, Wi 53211
> > phone (office): 1-414-229-4338
> > phone (lab): 414-229-3946
> > email: smar...@uwm.edu
> > https://uwm.edu/physics/people/schmidt-marius/
> > https://sites.uwm.edu/smarius/
> > https://www.bioxfel.org/
> > Nature News and Views: https://www.nature.com/articles/d41586-023-00504-4
> >
> > From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> on behalf of Marin van
> > Heel <marin.vanh...@gmail.com>
> > Sent: Monday, October 7, 2024 11:24 AM
> > To: CCP4BB@JISCMAIL.AC.UK <CCP4BB@JISCMAIL.AC.UK>
> > Subject: [ccp4bb] Review: Linearity and Resolution in X-Ray Crystallography
> > and Electron Microscopy
> > Dear All,
> >
> > Sayan Bhakta and I have recently posted the preprint of a review on
> > resolution and linearity which will appear in a book to be launched on the
> > 16th of October 2024.
> > ( https://doi.org/10.1201/9781003326106 ). It is the first Cryo-EM review
> > that I have been involved in for 25 years.
> > In our preparation, I was quite amazed about what other authors wrote (or
> > did not write) in their many reviews on these matters.
> > For example, I missed any serious discussion about resolution metrics in
> > X-ray crystallography, which technique is fundamentally non-linear.
> > Linearity is a prerequisite for defining the resolution of any instrument.
> > The iterative refinements applied in X-ray crystallography (and sometimes
> > Cryo-EM) makes that all Phase-residuals and R-factors or fixed threshold
> > values cannot be used to compare the results of independently conducted
> > experiments. What is an obvious consequence of the lack of universality of
> > such metrics like phase-residuals and R-factors, is that they cannot be
> > used outside of the immediate context in which they were defined, like
> > X-ray crystallography or structural biology. In contrast, the
> > Fourier-Ring-Correlation (FRC); Fourier-Shell-Correlation (FSC) and their
> > recent successors: the Fourier-Ring-Information (FRI) and the
> > Fourier-Shell-Information (FSI), plus their integrated versions, are
> > universal metrics that are applicable to all fields of science where 2D and
> > 3D data are dealt with!
> >
> > https://doi.org/10.31219/osf.io/5empt
> >
> > Have fun reading it!
> >
> > Marin
> >
> >
> >
> >
> >
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>
> -----
> Randy J. Read
> Department of Haematology, University of Cambridge
> Cambridge Institute for Medical Research Tel: +44 1223 336500
> The Keith Peters Building
> Hills Road E-mail:
> rj...@cam.ac.uk
> Cambridge CB2 0XY, U.K.
> www-structmed.cimr.cam.ac.uk
>
>
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-----
Randy J. Read
Department of Haematology, University of Cambridge
Cambridge Institute for Medical Research Tel: +44 1223 336500
The Keith Peters Building
Hills Road E-mail:
rj...@cam.ac.uk
Cambridge CB2 0XY, U.K.
www-structmed.cimr.cam.ac.uk
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