Combining all maps from a map series from 3DVA would be equivalent to taking the "consensus" map before 3DVA was applied, I believe (it depends what one means by "combine"). This map is blurry, since it results from aligning images of particles that all have slightly different conformations (and therefore can never align perfectly). So, doing this would cancel all the benefits of running 3DVA.
The same applies with cryoDRGN, it would not be useful to average together all the different states it found in a heterogeneous set of particles.
And to answer this earlier question:
Also.. just curious -- what is "3D variability of this map"? Is this one map that is a composition of several map or an ensemble of maps?
The big picture is that 3DVA is a PCA trying to find the major ways in which 2D particle images differ. Once principal components of variability are identified, it can then generate maps that are linear interpolations between observed particles, taken along the principal components. What is most often done in practice is to generate a series of maps traversing the first one or two principal components (or as many as you want until you explain most of the variability in the data). This can often identify hinge motions in a complex, or similar large-scale conformational changes. Now, because these maps are linear interpolations, they can sometimes show unphysical features, so I am not sure refining a model against these maps would work well. But it would with maps from cryoDRGN, since it does no such interpolation and can even generate maps that are guaranteed to be supported by observed data.
This is very simplified, I am no expert in computational methods. If you want to understand better what is reasonable to do with these maps, you need to know how they are produced, and the two papers I pointed to in my previous message explain this in detail.
I hope this helps,
Guillaume
On 13 Jan 2022, at 17:40, Pavel Afonine mailto:[email protected]> wrote:
Hi,
good discussion, thanks!
Instead of having a series of maps would it make sense to combine all these maps into one composite map, and then refine one atomic model against this composite map, and model variability using alternative conformations (very much like in crystallography)?
If that's a possible route then all is needed is a tool to combine the maps and phenix.real_space_refine can already handle models with alternative conformations (can refine occupancies in real space).
Pavel
On 1/13/22 08:17, Oliver Clarke wrote:
Hi,
Just to add my two cents, I agree this would be really useful for a lot of folks. Analysis of continuously distributed variability is very common these days in cryoEM, and having a way to jointly refine an ensemble of models against a series of maps would be very handy. Cryodrgn, 3D-VA in cryosparc, ManifoldEM, multibody refinement in relion - there are many tools now for generating a series of density maps potentially corresponding to conformational modes, so having the capacity in phenix to refine models against each map would be very helpful.
Cheers
Oli
Message: 1
Date: Wed, 12 Jan 2022 10:36:27 +0100
From: vincent Chaptal mailto:[email protected]>
To: Guillaume Gaullier mailto:[email protected]>, Pavel Afonine
mailto:[email protected]>
Cc: PHENIX user mailing list mailto:[email protected]>
Subject: Re: [phenixbb] refinement of an ensemble of structures ->
cryoEM variability
Message-ID: mailto:[email protected]>
Content-Type: text/plain; charset="utf-8"; Format="flowed"
Hi Guillaume,
thanks for the backup.
It's exactly my feeling also.
Best
Vincent
Le 12/01/2022 ? 10:09, Guillaume Gaullier a ?crit?:
Hi,
I am guessing what we are talking about here are the maps generated by
cryoSPARC 3D variability analysis. See: Punjani A & Fleet DJ (2021) 3D
Variability Analysis: Resolving continuous flexibility and discrete
heterogeneity from single particle cryo-EM.?Journal of Structural
Biology: 107702 https://doi.org/10.1016/j.jsb.2021.107702
But this is not the only program that generates series of maps to
describe continuous heterogeneity from single-particle cryoEM images,
see also cryoDRGN:?Zhong ED, Bepler T, Berger B & Davis JH (2021)
CryoDRGN: reconstruction of heterogeneous cryo-EM structures using
neural networks.?Nature Methods: 1?10
https://doi.org/10.1038/s41592-020-01049-4
Except some ideally rigid particles like apoferritin, pretty much
everything shows some degree of flexibility that generates continuous
heterogeneity in cryoEM images. So, my feeling is that a user-friendly
program to fit a series of models (ideally, auto-generated from a
single starting model) to a map series is probably going to be a
standard requirement pretty soon for typical single-particle cryoEM
projects.
Cheers,
Guillaume
On 11 Jan 2022, at 17:16, Pavel Afonine wrote:
Hi Vincent,
this looks like a very specialized task that I've never heard of
before! We can add a tool to do that if this becomes something that
more than one person does more than once. Meanwhile, a simple script
in a language of your?preference (python, linux shell, etc) should do
the job. I can help with a script if needed, let me know!
Also.. just curious -- what is "3D variability of this map"? Is this
one map that is a composition of several map or an ensemble of maps?
Pavel
On 1/11/22 01:48, vincent Chaptal wrote:
Hi Phenix-ers,
I thought to ask for something that I believe you have already
implemented, but I'm not sure of the best tool to use.
I have a cryoEM map where I refine my "high resolution" structure. I
also have the 3D variability of this map that shows?several maps
varying around the consensus high-res map. I want to refine an
ensemble (20) of structures, one for every 20?maps around the
consensus map.
Is there a tool in phenix to do this?
I could refine individually the high-res structure into each map
incrementally; since every map differs a little from the?original
one, Real-space-refinement could move the structure a little at a
time. Then I could combine all the PDBs in an?ensemble?
A tool to refine variability would be very useful. Input could be a
PDB and an ensemble of maps, and output would be all the?PDBs combined?
Thank you.
All the best
Vincent
--
Vincent Chaptal, PhD
Director of GdR APPICOM
Drug Resistance and Membrane Proteins Lab
MMSB -UMR5086
7 passage du Vercors
69007 LYON
FRANCE
+33 4 37 65 29 01
http://www.appicom.cnrs.fr
http://mmsb.cnrs.fr/en/
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MMSB -UMR5086
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+33 4 37 65 29 01
http://www.appicom.cnrs.fr
http://mmsb.cnrs.fr/en/