what about if you run a 2-D FFT rather than 2-D FFT, if your hand drawing map 
in on a 2-D paper?

> On Apr 28, 2023, at 10:48 AM, James Holton <[email protected]> wrote:
> 
> Its still April, but this one isn't a joke.
> 
> The smiley-face electron density in the left panel of the attached image has 
> the remarkable property that any attempt to sharpen or blur the map turns it 
> into the frowny-face on the right.  If you'd like to try this yourself, the 
> hidden_frown.map file is available in this tarball:
> https://bl831.als.lbl.gov/~jamesh/bugreports/fft_042423.tgz
> 
> In fact, any use of an FFT, even with the sharpening B set to zero, turns the 
> smiley into a frowny face. There is no way to get the smiley face back 
> (except opening the file again).  Yes, that's right, even just a simple 
> back-and-forth FFT: turning this hidden_frown.map into structure factors and 
> then back into a map again, gives you a frowny face.  This happens using 
> coot, ccp4 and phenix.
> 
> Wait, what!?  Isn't a Fourier transform supposed to preserve information? As 
> in: you can jump back and forth between real and reciprocal space with 
> impunity? Without introducing error?  Well, yes, it is SUPPOSED to work like 
> that, but the 3D FFT algorithms of structural biology have a ... quirk. If 
> you start with structure factors and make a map out of them, you can convert 
> it back-and-forth as often as you want with 100% preservation of information. 
>  However, if you start with a real-space map (such as from cryoEM), a 
> back-and-forth conversion gives you a different map. This new map can then be 
> transformed back-and-forth all you want and be 100% preserved. It has been 
> "christened" by the FFT, but it is not the same as the starting map, which is 
> impossible to recover from the FFT-transformed data. Information has been 
> lost.  It is fine for crystallography (which starts with structure factors), 
> but for techniques such as cryoEM that start with maps, using an FFT changes 
> the data.
> 
> What information is being lost?  Sharp edges. These turn into ripples 
> covering all of real and reciprocal space. Do real-world data have sharp 
> edges?  Well, the all-or-nothing masks we use to model bulk solvent are one 
> example. Also, if you "mask off" otherwise smooth density with an 
> all-or-nothing mask, you will get similar ripples.  Another example of a 
> sharp edge might be the large changes between adjacent pixels you see when a 
> single electron hits a detector. For example, if you make a map with just one 
> non-zero voxel and run it back-and-forth through FFT you will find that voxel 
> loses from 50% to 99% of its value (depending on the size of the map).  How 
> much does this actually impact cryo-EM data?  That is my question.
> 
> What evil magic did I wield to make this map?  Well, I drew a smiley and 
> frowny face by hand, converted them to maps, and then I generated random 
> noise within the boundaries of the smiley face. I ran this noisy map 
> back-and-forth through FFT, and then subtracted the map that survives the FFT 
> from the pre-FFT map.  This cheshire_smile.map has the interesting property 
> that all of the structure factors calculated from it are zero. It has an RMSD 
> of 1.4, but after a back-and-forth FFT this RMSD drops to 1e-7.  I generated 
> the hidden_frown.map by simply summing the frowny.map with cheshire_smile.map.
> 
> But isn't this map getting less noisy? Yes it is, but the interpretation 
> clearly changes as well.
> 
> Why does this happen?  It is because of a finite resolution cutoff. Oh! What 
> a relief! You don't have super-high resolution, do you? Well, no, almost 
> nobody has signal out beyond 1.0 A, but we do have noise.  In diffraction 
> data this noise is removed by simply not measuring it.  For map data, 
> however, the problem is that noise at very high frequencies (small-number 
> resolutions) is hard to avoid. This is because of another phenomenon NMR 
> spectroscopists are very familiar with: aliasing, or "folding".  If any 
> high-spatial frequency noise exists above half the sampling rate (or "Nyquist 
> frequency") it still gets recorded, but shows up in a lower-frequency Fourier 
> coefficient. It is not possible to remove such aliasing noise after 
> digitization. Upon discretization of the signal (FFT or no) all these high 
> frequencies join with lower frequency terms, and so survive any low-pass 
> filtering. Darn.
> 
> Why am I bringing this up?  Because if there is noise out beyond the FFT 
> resolution limit it implies there is also noise out beyond the 
> Nyquist-Shannon limit as well. If that is the case, direct-space imaging data 
> may be a lot noisier than it needs to be. In general, in digital signal 
> processing of things like sound an analog low-pass filter is always installed 
> at the input of any digitizer.  Perhaps this is why de-focusing works better 
> than being at focus?
> 
> What is the solution? Well, for things like the bulk solvent mask I'd say 
> some real-space "feathering" is called for before performing FFTs.  Same goes 
> for masked density like that used to compute CCmask. It may also be worth 
> looking into the digitization process of "image first" structural biology 
> methods?
> 
> My question for the BB:  can someone explain how Nyquist folding is handled 
> in cryoEM data processing?
> 
> -James Holton
> MAD Scientist
> 
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