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 [[log in to unmask]]
Sent: Wednesday, January 27, 2016 1:10 PM
To: Nancy Meyer
Cc: [log in to unmask]
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
> Thank you for the response! I'm an idiot and sent you star files...
> attached now are screenshots of representative particles and early
> classes. Also, two images showing some of the worst background variation
> in the orig micrographs.
>
> The micrographs show more than just simple gradients: 1) flatfields
> weren't always working during collection so you can also see distinct top
> and bottom zones in addition to general left/right gradient, and 2) the
> second half of the data include BLACK gold fiducials. Guessing the latter
> could be addressed through the --black_dust option. I may be out of luck
> with the former -- it's probably not a common problem.
>
> Most basically, I'd like to know whether, for a properly done
> normalization, I should expect to see none of that variation I'm seeing in
> the particles now. I can't recall ever noticing it in earlier datasets.
>
> And, yes, had since figured how to run mpi version (set num MPI procs!).
> I'm using SLURM job handler and learning :-) Thank you again for any
> thoughts!
>
> Best,
> Nancy
>
> Nancy Meyer
> Research Associate
> Oregon Health and Science University
> Department of Biochemistry and Molecular Biology
> Chapman Lab, MRB 534
> Ph: 503-494-1615
> Fx: 503-494-8393
>
> ________________________________________
> From: Sjors Scheres [[log in to unmask]]
> Sent: Wednesday, January 27, 2016 12:05 AM
> To: Nancy Meyer
> Cc: [log in to unmask]
> Subject: Re: [ccpem] Adequate particle normalization prior to 2D
> classification?
>
> Hi Nancy,
> In 1.4, normalization should include ramping background correction. Are
> these images which you send? What format are they in? I cannot seem to
> open them.
> best,
> Sjors
> PS: shouldn't you run relion_preprocess_mpi instead of relion_preprocess?
> (this will not solve your issue)
>> Hi all,
>>
>> I'm concerned about whether a particle set is being normalized properly
>> during particle extraction in Relion 1.4. Attached is a star file of
>> representative particles (icosahedral virus). At the bottom is my
>> particle
>> extraction command.
>>
>> Backgrounds seem to vary quite a bit, even when boxes are not over the
>> edge of the micrograph. I should say a good number of the micrographs
>> show
>> a regular light/dark gradient across the image (due to acquisition
>> issues), and that each contain at least a single row of "dead" pixels.
>> Particles were extracted from raw micrographs following CTF estimation
>> in
>> Relion using .box coord files determined in EMAN2, so these images
>> should
>> not have any normalization done to them except that specified by
>> Relion's
>> --norm option.
>>
>> Concerned that intensity variation will be problematic downstream -- can
>> anyone suggest Relion-compatible methods to take into account the
>> background gradients (if that's the culprit), or am I doing something
>> more
>> obviously wrong? Thanks for any input!
>>
>> Command for particle extraction:
>> -bash-4.1$ srun --nodes 5 --ntasks-per-node 24 relion_preprocess --o
>> ptcls
>> --mic_star micrographs_ctf.star --coord_suffix ".box" --extract
>> --extract_size 384 --norm --bg_radius 190 --white_dust -1 --black_dust
>> -1
>> --coord_files "Micrographs/*.box"
>>
>> -- particles themselves are approximately 260A diam
>> -- also attached an example of early 2D classes showing background
>> variation
>>
>> Thanks!!
>>
>
>
> --
> Sjors Scheres
> MRC Laboratory of Molecular Biology
> Francis Crick Avenue, Cambridge Biomedical Campus
> Cambridge CB2 0QH, U.K.
> tel: +44 (0)1223 267061
> http://www2.mrc-lmb.cam.ac.uk/groups/scheres
>
>
--
Sjors Scheres
MRC Laboratory of Molecular Biology
Francis Crick Avenue, Cambridge Biomedical Campus
Cambridge CB2 0QH, U.K.
tel: +44 (0)1223 267061
http://www2.mrc-lmb.cam.ac.uk/groups/scheres
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