[ccp4bb] Data acquisition (MX) positions at Diamond Light Source

[Graeme Winter]

Dear All,

We have software engineer posts open at the moment at Diamond Light Source in 
the MX data acquisition team (i.e. beamline user software) - details at

http://www.diamond.ac.uk/Careers/Vacancies/All/119_17_CH.html

It's an exiting time at the moment, with new beamlines being built, increasing 
levels of automation and ever more challenging experiments being performed, and 
the beamline software is the user's interface to all of this - so please come & 
be part of these developments :o)

Best wishes Graeme

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Re: [ccp4bb] Basic Crystallography/Imaging Conundrum

[Dale Tronrud]

   Ethan and I apparently agree that anomalous scattering is "normal"
and Friedel's Law is just an approximation.  I'll presume that your
"unique" is assuming otherwise and your 62,500 reflections only include
half of reciprocal space.  The full sphere of data would include 125,000
reflections.  Since the cube root of 125,000 is 50 you get a range of
indices from -25 to +25 which would give you 2 A resolution, which is
still far from your hope of 1 A.

   For your test case of 1 A resolution with 50 A cell lengths you want
your indices to run from -50 to +50 giving a box of reflections in
reciprocal space 101 spots wide in each direction and a total of 101^3 =
1,030,301 reflections. (or 515,150.5 reflections for your Friedel unique
with the "half" reflection being the F000 which would then be purely
real valued.)

   Assuming you can fit your structure factors into 16 bits (You had
better not have many more than 10,000 atoms if you don't want your F000
to overflow.) the information content will be 1,030,301 * 2 * 16 bits
(The "2" because they are complex.) giving 32,969,632 bits.

   If you spread this same amount of information across real space you
will have 1,030,301 complex density values in a 50x50x50 A space giving
a sampling rate along each axis of 101 samples/unit cell.

   Complex density values?  The real part of the density is what we call
the electron density and the imaginary part we call the anomalous
density.  If there is no anomalous scattering then Friedel's Law holds
and the number of unique reflections is cut in half and the density
values are purely real valued - The information content in both spaces
is cut in half and they remain equal.

   By sampling your unit cell with 101 samples their rate is half that
of the wavelength of the highest frequency reflection.  (e.q. a sampling
rate of 0.5 A for 1 A resolution data)  This is, of course, the Nyquist
Theorem which states that you have to sample at twice the frequency of
the highest resolution Fourier coefficient.

  This is exactly how an FFT works.  It allocates the memory required to
store the structure factors and it returns the map in that same array -
The number of bytes is unchanged.  It also guarantees that the
calculation is reversible as no information is lost in either direction.

   So, why does your blocky image look so bad?  First you have sampled
too coarsely.  You should have twice the sampling rate in each direction.

   The next point is more subtle.  You are displaying each voxel as a
block.  This is not correct.  The sharp lines that occur at the
boundaries between the blocks is a high frequency feature which is not
consistent with a 1 A resolution image.  Your sample points should be
displayed at discrete points since they are not the average density
within a block but the value of the density at one specific point.

   What is the density of the map between the sampled points?  The
Fourier series provides all the information needed to calculate them and
you can calculate values for as fine a sampling rate as you like, just
remember that you are not adding any more information because these new
points are correlated with each other.

   If you have only the samples of a map and want to calculate Fourier
coefficients there are many sets of Fourier coefficients that will
reproduce the sampled points equally well.  We specify a unique solution
in the FFT by defining that all reflections of resolution higher than 1
A must be identically equal to zero.  When you calculate a map from a
set of coefficients that only go to 1 A resolution this is guaranteed.

   When you are calculating coefficients from any old map you had better
ensure that the map you are sampling does not contain information of a
higher resolution than twice your sampling rate.  This is a problem when
calculating Fcalc from an atomic model.  You calculate a map from the
model and FFT it, but you can't sample that map at 1/2 the resolution of
your interest.  You must sample that map much more finely because an
atomic model implies Fourier coefficients of very high resolution.
(Otherwise phase extension would be impossible)  This problem was
discussed in detail in Lynn Ten Eyck's 1976 paper on Fcalc FFT's but is
often forgotten.  Gerard Bricogne's papers on NCS averaging from the
1970's also discusses these matters in great depth.

   In summary, your blocky picture (even with double sampling) is not a
valid representation because it is not blurry like a 1 A resolution map
should be.  To create an accurate image you need to oversample the map
sufficiently to prevent the human eye from detecting aliasing artifacts
such as the straight lines visible in your blocky picture.  This
requires very fine sampling because the eye is very sensitive to
straight lines.  When using a map for any purpose other than FFTing you
will need to oversample the map by some amount to prevent aliasing
artifacts and the amount of oversampling will depend on what you are
doing to 

Re: [ccp4bb] Basic Crystallography/Imaging Conundrum

[Ethan Merritt]

On Friday, 10 November 2017 05:29:09 Keller, Jacob wrote:
> >>62500 is < 40^3, so ±20 indices on each axis.
> 50Å / 20 = 2.5Å,  so not quite 2.5Å resolution
> 
> Nice--thanks for calculating that. Couldn't remember how to do it off-hand, 
> and I guess my over-estimate comes from most protein crystals having some 
> symmetry. I don't really think it affects the question though--do you?
> 
> >>All that proves is that assigning each 1x1x1 voxel a separate density value 
> >>is a very inefficient use of information.  Adjacent voxels are not 
> >>independent, and no possible assignment of values will get around the 
> >>inherent blockiness of the representation.
> 
> Not sure what this means--what is the precise definition or measure of 
> "efficient use of information?" Like a compression algorithm? 

If it helps you to think of it that way, fine.
Suppose it is possible to compress a data set losslessly.
The information content is unchanged, but the compressed representation
is smaller than the original, so the information content per unit of size
is higher - a better use of space - hence "more efficient".

> Are diffraction data sets like compressed data?

Not the diffraction data, no.

But it is true that a truncated Fourier series is one way of compressing data.
Because of the truncation. it is a lossy, rather than lossless, compression.
An infinite series could give infinite resolution, but a truncated series is 
limited by the resolution of terms that are kept after truncation.

For example the compression used in JPEG is a truncated discrete cosine
transform (DCT), making JPEG files smaller than the original pixel-by-pixel 
image.

I'll throw a brain-teaser back at you.

As just noted, encoding the continuous electron density distribution in a
unit cell as a truncated Fourier series is essentially creating a JPEG image of
the original.  It is lossy, but as we know from experience JPEG images are 
pretty good at retaining the "feel" of the origin even with fairly severe
truncation.

But newer compression algorithms like JPEG2000 don't use DCTs,
instead they use wavelets.   I won't get sidetracked by trying to describe
wavelets, but the point is that by switching from a series of cosines to
a series of wavelets you can get higher compression.  They are
more efficient in representing the original data at a selected resolution.   

So here's the brain-teaser:
Why does Nature use Fourier transforms rather than Wavelet transforms?
Or does she?
Have we crystallographers been fooled into describing our experiments
in terms of Fourier transforms when we could do better by using wavelets
or some other transform entirely?

Ethan
 


> Also, the "blockiness" of representation is totally ancillary--you can do all 
> of the smoothing you want, I think, and the voxel map will still be basically 
> lousy. No?

> >>I know!  Let's instead of assigning a magnitude per voxel, let's assign a 
> >>magnitude per something-resolution-sensitive, like a sin wave.   Then for 
> >>each hkl measurement we get one sin wave term.   Add up all the sine waves 
> >>and what do you get?  Ta da.  A nice map.
> 
> It was good of proto-crystallographers to invent diffraction as a way to 
> apply Fourier Series. I don't know--it seems funny to me that somehow 
> diffraction is able to harness "efficient information use," whereas the voxel 
> map is not. I am looking for more insight into this.
> 
> >>Aren't Fourier series marvelous?
> 
> Well, I have always liked FTs, but your explanations are not particularly 
> enlightening to me yet.
> 
> I will re-iterate that the reason I brought this up is that the imaging world 
> might learn a lot from crystallography's incredible extraction of all 
> possible information through the use of priors and modelling.
> 
> Also, I hope you noticed that all of the parameters about the 
> crystallographic data set were extremely optimistic, and in reality the 
> information content would be far less.
> 
> One could compare the information content of the derived structure to that of 
> the measurements to get a metric for "information extraction," perhaps, and 
> this could be applied across many types of experiments in different fields. I 
> nominate crystallography for the best ratio.
> 
> JPK
> 
> 
> 
>  
> > Assuming that it is apt, however: is this a possible way to see the power 
> > of all of our Bayesian modelling? Could one use our modelling tools on such 
> > a grainy picture and arrive at similar results?
> >
> > Are our data sets really this poor in information, and we just model the 
> > heck out of them, as perhaps evidenced by our scarily low data:parameters 
> > ratios?
> > 
> > My underlying motivation in this thought experiment is to illustrate the 
> > richness in information (and poorness of modelling) that one achieves in 
> > fluorescence microscopic imaging. If crystallography is any measure of the 
> > power of modelling, one could really go to town on some of these terabyte 

Re: [ccp4bb] Basic Crystallography/Imaging Conundrum

[Keller, Jacob]

>>62500 is < 40^3, so ±20 indices on each axis.
50Å / 20 = 2.5Å,  so not quite 2.5Å resolution

Nice--thanks for calculating that. Couldn't remember how to do it off-hand, and 
I guess my over-estimate comes from most protein crystals having some symmetry. 
I don't really think it affects the question though--do you?

>>All that proves is that assigning each 1x1x1 voxel a separate density value 
>>is a very inefficient use of information.  Adjacent voxels are not 
>>independent, and no possible assignment of values will get around the 
>>inherent blockiness of the representation.

Not sure what this means--what is the precise definition or measure of 
"efficient use of information?" Like a compression algorithm? Are diffraction 
data sets like compressed data?

Also, the "blockiness" of representation is totally ancillary--you can do all 
of the smoothing you want, I think, and the voxel map will still be basically 
lousy. No?

>>I know!  Let's instead of assigning a magnitude per voxel, let's assign a 
>>magnitude per something-resolution-sensitive, like a sin wave.   Then for 
>>each hkl measurement we get one sin wave term.   Add up all the sine waves 
>>and what do you get?  Ta da.  A nice map.

It was good of proto-crystallographers to invent diffraction as a way to apply 
Fourier Series. I don't know--it seems funny to me that somehow diffraction is 
able to harness "efficient information use," whereas the voxel map is not. I am 
looking for more insight into this.

>>Aren't Fourier series marvelous?

Well, I have always liked FTs, but your explanations are not particularly 
enlightening to me yet.

I will re-iterate that the reason I brought this up is that the imaging world 
might learn a lot from crystallography's incredible extraction of all possible 
information through the use of priors and modelling.

Also, I hope you noticed that all of the parameters about the crystallographic 
data set were extremely optimistic, and in reality the information content 
would be far less.

One could compare the information content of the derived structure to that of 
the measurements to get a metric for "information extraction," perhaps, and 
this could be applied across many types of experiments in different fields. I 
nominate crystallography for the best ratio.

JPK



 
> Assuming that it is apt, however: is this a possible way to see the power of 
> all of our Bayesian modelling? Could one use our modelling tools on such a 
> grainy picture and arrive at similar results?
>
> Are our data sets really this poor in information, and we just model the heck 
> out of them, as perhaps evidenced by our scarily low data:parameters ratios?
> 
> My underlying motivation in this thought experiment is to illustrate the 
> richness in information (and poorness of modelling) that one achieves in 
> fluorescence microscopic imaging. If crystallography is any measure of the 
> power of modelling, one could really go to town on some of these terabyte 5D 
> functional data sets we see around here at Janelia (and on YouTube).
> 
> What do you think?
> 
> Jacob Keller
> 
> +
> Jacob Pearson Keller
> Research Scientist / Looger Lab
> HHMI Janelia Research Campus
> 19700 Helix Dr, Ashburn, VA 20147
> (571)209-4000 x3159
> +
> 

--
Ethan A Merritt, Dept of Biochemistry
Biomolecular Structure Center,  K-428 Health Sciences Bldg
MS 357742,   University of Washington, Seattle 98195-7742

Re: [ccp4bb] Basic Crystallography/Imaging Conundrum

[Ethan Merritt]

On Friday, 10 November 2017 00:10:22 Keller, Jacob wrote:
> Dear Crystallographers,
> 
> I have been considering a thought-experiment of sorts for a while, and wonder 
> what you will think about it:
> 
> Consider a diffraction data set which contains 62,500 unique reflections from 
> a 50 x 50 x 50 Angstrom unit cell, with each intensity measured perfectly 
> with 16-bit depth. (I am not sure what resolution this corresponds to, but it 
> would be quite high even in p1, I think--probably beyond 1.0 Angstrom?).

Meh. 
62500 is < 40^3, so ±20 indices on each axis.
50Å / 20 = 2.5Å,  so not quite 2.5Å resolution


> Thus, there are 62,500 x 16 bits (125 KB) of information in this alone, and 
> there is an HKL index associated with each intensity, so that I suppose 
> contains information as well. One could throw in phases at 16-bit as well, 
> and get a total of 250 KB for this dataset.
> 
> Now consider an parallel (equivalent?) data set, but this time instead of 
> reflection intensities you have a real space voxel map of the same 50 x 50 x 
> 50 unit cell consisting of 125,000 voxels, each of which has a 16-bit 
> electron density value, and an associated xyz index analogous to the hkl 
> above. That makes a total of 250 KB, with each voxel a 1 Angstrom cube. It 
> seems to me this level of graininess would be really hard to interpret, 
> especially for a static picture of a protein structure. (see attached: top is 
> a ~1 Ang/pixel down-sampled version of the image below).

All that proves is that assigning each 1x1x1 voxel a separate density value is 
a very
inefficient use of information.  Adjacent voxels are not independent, and no 
possible
assignment of values will get around the inherent blockiness of the 
representation.

I know!  Let's instead of assigning a magnitude per voxel, let's assign a 
magnitude per
something-resolution-sensitive, like a sin wave.   Then for each hkl 
measurement we get
one sin wave term.   Add up all the sine waves and what do you get?  Ta da.  A 
nice map.
 
> Or, if we wanted smaller voxels still, let's say by half, we would have to 
> reduce the bit depth to 2 bits. But this would still only yield half-Angstrom 
> voxels, each with only four possible electron density values.
> 
> Is this comparison apt? Off the cuff, I cannot see how a 50 x 50 pixel image 
> corresponds at all to the way our maps look, especially at around 1 Ang 
> resolution. Please, if you can shoot down the analogy, do.

Aren't Fourier series marvelous?

 
> Assuming that it is apt, however: is this a possible way to see the power of 
> all of our Bayesian modelling? Could one use our modelling tools on such a 
> grainy picture and arrive at similar results?
>
> Are our data sets really this poor in information, and we just model the heck 
> out of them, as perhaps evidenced by our scarily low data:parameters ratios?
> 
> My underlying motivation in this thought experiment is to illustrate the 
> richness in information (and poorness of modelling) that one achieves in 
> fluorescence microscopic imaging. If crystallography is any measure of the 
> power of modelling, one could really go to town on some of these terabyte 5D 
> functional data sets we see around here at Janelia (and on YouTube).
> 
> What do you think?
> 
> Jacob Keller
> 
> +
> Jacob Pearson Keller
> Research Scientist / Looger Lab
> HHMI Janelia Research Campus
> 19700 Helix Dr, Ashburn, VA 20147
> (571)209-4000 x3159
> +
> 

-- 
Ethan A Merritt, Dept of Biochemistry
Biomolecular Structure Center,  K-428 Health Sciences Bldg
MS 357742,   University of Washington, Seattle 98195-7742

Re: [ccp4bb] reject images based on Rmerge

[Kay Diederichs]

As Eleanor and Gerard explained - perhaps there is a reason that some frames 
are really bad.

But it could just as well be that the crystal diffracts anisotropically, and 
those frames with high Rmerge correspond to a weak region of reciprocal space. 
In this case, it would be quite counterproductive to remove them, since the 
best you can do is to increase the multiplicity, which should lead to improved 
accuracy of the data.

The program xdscc12 allows you to find out the influence of frames on the CC1/2 
in a user-specified number of resolution range. This would tell you if those 
frames deteriorate your merged data, or not. Rmerge is the wrong value to look 
at.

best,

Kay

On Thu, 9 Nov 2017 14:04:36 -0500, CPMAS Chen  wrote:

>Hi All,
>
>Is there a way to reject diffraction images based on Rmerge?
>
>When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
>truncated data. However, there is quite some images with high Rmerge, say
>larger than 1. Is there a keyword I can use to reject these images based a
>Rmerge cut-off, say 0.6?
>
>Thanks!
>
>Charles
>
>--
>
>***
>
>Charles Chen, Ph. D
>
>Research Associate
>
>University of Pittsburgh School of Medicine
>
>Department of Anesthesiology
>
>**
>

Re: [ccp4bb] Removing a ter line present in the middle of the chain

[John Berrisford]

If you output an mmCIF file directly from refmac this avoids the TER 
record problem.


just add this

"pdbout format mmcif"

to your refmac command and it will output an mmCIF which can be used 
directly for deposition to the PDB


see https://www.wwpdb.org/deposition/preparing-pdbx-mmcif-files

Regards

John

PDBe

On 07/11/2017 15:02, Bernhard Rupp wrote:

This TER business is a common lament generally surfacing upon deposition.
PDB demands TER only after a peptide chain, but refmac inserts
them liberally after HETATM chains and in between them if the HET
monomers are not consecutively numbered.

Example:
.
HETATM 4626  C8  NAG A 652  -7.708  54.612  47.885  1.00 66.94   C
HETATM 4627  O7  NAG A 652  -6.870  54.052  45.727  1.00 74.93   O
TER4628  NAG A 652
HETATM 4629 CL   CL  A 801  21.660  57.665  44.396  1.00 72.44  CL
HETATM 4630 CL   CL  A 802   9.893  42.272  48.748  1.00 44.08  CL
TER4631  CL  A 802
ATOM   4632  N   PHE B  11  24.376 -12.877  29.777  1.00 80.09   N
ATOM   4633  CA  PHE B  11  24.701 -14.037  28.894  1.00 80.63   C
.
I have a crude hack removes aberrant TERs but it is
in F90 and no guarantees whatsoever case someone wants it.

Best, BR

-Original Message-
From: CCP4 bulletin board [mailto:CCP4BB@JISCMAIL.AC.UK] On Behalf Of Marcin 
Wojdyr
Sent: Tuesday, November 7, 2017 5:33 AM
To: CCP4BB@JISCMAIL.AC.UK
Subject: Re: [ccp4bb] Removing a ter line present in the middle of the chain

On 7 November 2017 at 12:28, Eleanor Dodson 
<176a9d5ebad7-dmarc-requ...@jiscmail.ac.uk> wrote:

Something (Refmac? Coot?? mystery?) was labelling all atoms in MSE
residues as HETATM and that was a BAD THING..

I don't dispute this, but that's what the pdb spec from the PDB requires 
(HETATM for all non-standard residues).
Example: https://files.rcsb.org/view/5ABS.pdb

Marcin


--
John Berrisford
PDBe
European Bioinformatics Institute (EMBL-EBI)
European Molecular Biology Laboratory
Wellcome Trust Genome Campus
Hinxton
Cambridge CB10 1SD UK
Tel: +44 1223 492529

http://www.pdbe.org
http://www.facebook.com/proteindatabank
http://twitter.com/PDBeurope

Re: [ccp4bb] reject images based on Rmerge

[Gerard Bricogne]

Dear Charles,

 Eleanor is right: look at the images, and look also at the
processing output produced by XDS. If you find that too ASCII-looking,
then look at the graphs produced from these numbers by programs like
XDSGUI, XDSAPP and others. Our own autoPROC produces an extensive html
output (called "summary.html") that will contain all these graphs.

 In general you have to look at several of them simultanously to
figure out what went wrong. Your type of problem is often produced by
a bad crystal centring that causes the crystal to move out of the beam
in some ranges of images. In that case you can see that the number of
indexed spots as a function of image number goes down to worryingly
low values in certain ranges, and that the image scale factors and
B-factor have large excursions for those same ranges, that are also
the ranges where the Rmerge values end up quite high. In this case it
is just because spots on images made systematically weaker (and
therefore noisier) by the loss of centring had to be scaled up by
CORRECT/AIMLESS.

 If such is the case with your dataset, there is not much you can
do. Your only hope is to be lucky enough to have enough redundancy in
your raw data that the reflections on the useless images will have
been measured through symmetry equivalents on images for which the
crystal centring was good.

 It could also be that your crystals are very thin plates.


 With best wishes,
 
  Gerard.

--
On Thu, Nov 09, 2017 at 07:53:40PM +, Eleanor Dodson wrote:
> I think you need to look at the images.
> We found one case where the overall Rmerge didnt look too bad but there
> were horrendous streaks across many images. No idea what had happened but
> other crystals from the same batch were much better.
> 
> Eleanor
> 
> On 9 November 2017 at 19:26, CPMAS Chen  wrote:
> 
> > That is right. I had the data already and did not want to throw it away.
> >
> > On Thu, Nov 9, 2017 at 2:09 PM, Eleanor Dodson 
> > wrote:
> >
> >> I think you need to worry about why that has happened, rather than get an
> >> automated rejection criteria!
> >> There must be some problem in the data collection for that to happen..
> >>
> >> Eleanor
> >>
> >> On 9 November 2017 at 19:04, CPMAS Chen  wrote:
> >>
> >>> Hi All,
> >>>
> >>> Is there a way to reject diffraction images based on Rmerge?
> >>>
> >>> When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
> >>> truncated data. However, there is quite some images with high Rmerge, say
> >>> larger than 1. Is there a keyword I can use to reject these images based a
> >>> Rmerge cut-off, say 0.6?
> >>>
> >>> Thanks!
> >>>
> >>> Charles
> >>>
> >>> --
> >>>
> >>> ***
> >>>
> >>> Charles Chen, Ph. D
> >>>
> >>> Research Associate
> >>>
> >>> University of Pittsburgh School of Medicine
> >>>
> >>> Department of Anesthesiology
> >>>
> >>> **
> >>>
> >>>
> >>
> >
> >
> > --
> >
> > ***
> >
> > Charles Chen
> >
> > Research Associate
> >
> > University of Pittsburgh School of Medicine
> >
> > Department of Anesthesiology
> >
> > **

Re: [ccp4bb] reject images based on Rmerge

[Eleanor Dodson]

I think you need to look at the images.
We found one case where the overall Rmerge didnt look too bad but there
were horrendous streaks across many images. No idea what had happened but
other crystals from the same batch were much better.

Eleanor

On 9 November 2017 at 19:26, CPMAS Chen  wrote:

> That is right. I had the data already and did not want to throw it away.
>
> On Thu, Nov 9, 2017 at 2:09 PM, Eleanor Dodson 
> wrote:
>
>> I think you need to worry about why that has happened, rather than get an
>> automated rejection criteria!
>> There must be some problem in the data collection for that to happen..
>>
>> Eleanor
>>
>> On 9 November 2017 at 19:04, CPMAS Chen  wrote:
>>
>>> Hi All,
>>>
>>> Is there a way to reject diffraction images based on Rmerge?
>>>
>>> When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
>>> truncated data. However, there is quite some images with high Rmerge, say
>>> larger than 1. Is there a keyword I can use to reject these images based a
>>> Rmerge cut-off, say 0.6?
>>>
>>> Thanks!
>>>
>>> Charles
>>>
>>> --
>>>
>>> ***
>>>
>>> Charles Chen, Ph. D
>>>
>>> Research Associate
>>>
>>> University of Pittsburgh School of Medicine
>>>
>>> Department of Anesthesiology
>>>
>>> **
>>>
>>>
>>
>
>
> --
>
> ***
>
> Charles Chen
>
> Research Associate
>
> University of Pittsburgh School of Medicine
>
> Department of Anesthesiology
>
> **
>
>

Re: [ccp4bb] reject images based on Rmerge

[CPMAS Chen]

That is right. I had the data already and did not want to throw it away.

On Thu, Nov 9, 2017 at 2:09 PM, Eleanor Dodson 
wrote:

> I think you need to worry about why that has happened, rather than get an
> automated rejection criteria!
> There must be some problem in the data collection for that to happen..
>
> Eleanor
>
> On 9 November 2017 at 19:04, CPMAS Chen  wrote:
>
>> Hi All,
>>
>> Is there a way to reject diffraction images based on Rmerge?
>>
>> When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
>> truncated data. However, there is quite some images with high Rmerge, say
>> larger than 1. Is there a keyword I can use to reject these images based a
>> Rmerge cut-off, say 0.6?
>>
>> Thanks!
>>
>> Charles
>>
>> --
>>
>> ***
>>
>> Charles Chen, Ph. D
>>
>> Research Associate
>>
>> University of Pittsburgh School of Medicine
>>
>> Department of Anesthesiology
>>
>> **
>>
>>
>


-- 

***

Charles Chen

Research Associate

University of Pittsburgh School of Medicine

Department of Anesthesiology

**

Re: [ccp4bb] reject images based on Rmerge

[Eleanor Dodson]

I think you need to worry about why that has happened, rather than get an
automated rejection criteria!
There must be some problem in the data collection for that to happen..

Eleanor

On 9 November 2017 at 19:04, CPMAS Chen  wrote:

> Hi All,
>
> Is there a way to reject diffraction images based on Rmerge?
>
> When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
> truncated data. However, there is quite some images with high Rmerge, say
> larger than 1. Is there a keyword I can use to reject these images based a
> Rmerge cut-off, say 0.6?
>
> Thanks!
>
> Charles
>
> --
>
> ***
>
> Charles Chen, Ph. D
>
> Research Associate
>
> University of Pittsburgh School of Medicine
>
> Department of Anesthesiology
>
> **
>
>

[ccp4bb] reject images based on Rmerge

[CPMAS Chen]

Hi All,

Is there a way to reject diffraction images based on Rmerge?

When I processed my data with XDS, I use AIMLESS in CCP4 to get merged,
truncated data. However, there is quite some images with high Rmerge, say
larger than 1. Is there a keyword I can use to reject these images based a
Rmerge cut-off, say 0.6?

Thanks!

Charles

-- 

***

Charles Chen, Ph. D

Research Associate

University of Pittsburgh School of Medicine

Department of Anesthesiology

**

Re: [ccp4bb] double cell dimensions between P2 and C2

[Dale Tronrud]

   I agree with Phil.  A P2 crystal with nearly perfect
noncrystallographic translational symmetry (~1/2,~1/2,0) will look like
a C2 cell with twice the length along a and b and weak spots between the
indexed spots.  Look for those spots on your "C2" images.

Dale Tronrud

On 11/9/2017 3:06 AM, Phil Evans wrote:
> You should look critically at the indexing of the images for both cases. Does 
> the lattice interpret all spots, or are half of them missing
> 
> 
>> On 9 Nov 2017, at 10:02, Markus Heckmann  wrote:
>>
>> Dear all,
>>> From a small protein, gives crystals P2 with cell
>> Cell 53.16   65.73   72.8990  110.94  90
>> (has 3 molecules in the asymmetric unit). Tested with pointless. Does
>> not give any other possibility.
>>
>> Another crystal if the same protein, similar conditions:
>> C2
>> Cell 109.14  124.37   73.4290  111.75  90. This has 6
>> molecules in the a.s.u. Tested with pointless. Does not give any other
>> possibility.
>> The cell length a, b of C2 is twice that of P2.
>>
>> Is it usual to get such crystals from similar conditions or am I
>> missing something?
>>
>> Many thanks,
>> Mark
> 

Re: [ccp4bb] unit cell is double between 2 forms

[Bernhard Rupp]

The cells are related. You double 2 axes, giving 4x the P2 volume (not double).
You gain a C (translational centering in the ab plane) so you have 2x the asu 
content in C2.
Pointless tells you about the space group based on the indexed reflections,
so you might want to look at the images to decide whether the P2 indexing 
simply missed a 
(commensurate) superstructure with t=~(1/2, 1/2, 0). You can probably 
distinguish
a modulation in the zonal reflections h+k=2n. 

Stuff like this happens frequently, with minimal translocations switching from 
one 
crystal form to the other. Minor changes in crystallization conditions 
(additives?)
might stabilize one or the other. 

Also note that superstructure detectability is a matter of resolution. 
Deviations from a 
perfect translational symmetry (crystallographic) to NCS (loss of the element) 
are
more significant at high resolution, where the indexing may pick up the extra
spots but not at low resolution, where the symmetry still looks (almost) 
perfect 
(or, coming from the other side, not detect merging problems and assign higher 
symmetry). The transition from crystallographic symmetry to related NCS and
vice versa is a continuous one and often hard to detect.

Best, BR

-Original Message-
From: CCP4 bulletin board [mailto:CCP4BB@JISCMAIL.AC.UK] On Behalf Of Markus 
Heckmann
Sent: Thursday, November 9, 2017 2:28 AM
To: CCP4BB@JISCMAIL.AC.UK
Subject: [ccp4bb] unit cell is double between 2 forms

Dear all,
we crystallized a small protein, that gives crystals P2 with cell
Cell 53.16   65.73   72.8990  110.94  90
(has 3 molecules in the asymmetric unit). Tested with pointless. Does not give 
any other possibility.

The other crystal form of the same protein, similar conditions:
C2
Cell 109.14  124.37   73.4290  111.75  90. This has 6
molecules in the a.s.u. Tested with pointless. Does not give any other 
possibility.
The cell length a, b of C2 is twice that of P2.

Is it usual to get such crystals from similar conditions or am I missing 
something?

Many thanks,
Mark

Re: [ccp4bb] double cell dimensions between P2 and C2

[Andrew Leslie]

Dear Markus,

 I have seen something similar before, I think it was only 
one cell dimension that was changing (and not the lattice type), but it could 
double or triple the cell edge, crystals grown in very similar conditions, 
impossible to tell from morphology what the cell would be, so such things can 
happen.

Cheers,

Andrew
> On 9 Nov 2017, at 10:02, Markus Heckmann  wrote:
> 
> Dear all,
>> From a small protein, gives crystals P2 with cell
> Cell 53.16   65.73   72.8990  110.94  90
> (has 3 molecules in the asymmetric unit). Tested with pointless. Does
> not give any other possibility.
> 
> Another crystal if the same protein, similar conditions:
> C2
> Cell 109.14  124.37   73.4290  111.75  90. This has 6
> molecules in the a.s.u. Tested with pointless. Does not give any other
> possibility.
> The cell length a, b of C2 is twice that of P2.
> 
> Is it usual to get such crystals from similar conditions or am I
> missing something?
> 
> Many thanks,
> Mark

Re: [ccp4bb] double cell dimensions between P2 and C2

[Phil Evans]

You should look critically at the indexing of the images for both cases. Does 
the lattice interpret all spots, or are half of them missing


> On 9 Nov 2017, at 10:02, Markus Heckmann  wrote:
> 
> Dear all,
>> From a small protein, gives crystals P2 with cell
> Cell 53.16   65.73   72.8990  110.94  90
> (has 3 molecules in the asymmetric unit). Tested with pointless. Does
> not give any other possibility.
> 
> Another crystal if the same protein, similar conditions:
> C2
> Cell 109.14  124.37   73.4290  111.75  90. This has 6
> molecules in the a.s.u. Tested with pointless. Does not give any other
> possibility.
> The cell length a, b of C2 is twice that of P2.
> 
> Is it usual to get such crystals from similar conditions or am I
> missing something?
> 
> Many thanks,
> Mark

[ccp4bb] AW: [ccp4bb] double cell dimensions between P2 and C2

[Herman . Schreuder]

Dear Mark,

It does happen, even that two crystals from the same drop (everything 
identical) have different space groups.

Best,
Herman

-Ursprüngliche Nachricht-
Von: CCP4 bulletin board [mailto:CCP4BB@JISCMAIL.AC.UK] Im Auftrag von Markus 
Heckmann
Gesendet: Donnerstag, 9. November 2017 11:02
An: CCP4BB@JISCMAIL.AC.UK
Betreff: [EXTERNAL] [ccp4bb] double cell dimensions between P2 and C2

Dear all,
From a small protein, gives crystals P2 with cell
Cell 53.16   65.73   72.8990  110.94  90
(has 3 molecules in the asymmetric unit). Tested with pointless. Does not give 
any other possibility.

Another crystal if the same protein, similar conditions:
C2
Cell 109.14  124.37   73.4290  111.75  90. This has 6
molecules in the a.s.u. Tested with pointless. Does not give any other 
possibility.
The cell length a, b of C2 is twice that of P2.

Is it usual to get such crystals from similar conditions or am I missing 
something?

Many thanks,
Mark

[ccp4bb] unit cell is double between 2 forms

[Markus Heckmann]

Dear all,
we crystallized a small protein, that gives crystals P2 with cell
Cell 53.16   65.73   72.8990  110.94  90
(has 3 molecules in the asymmetric unit). Tested with pointless. Does
not give any other possibility.

The other crystal form of the same protein, similar conditions:
C2
Cell 109.14  124.37   73.4290  111.75  90. This has 6
molecules in the a.s.u. Tested with pointless. Does not give any other
possibility.
The cell length a, b of C2 is twice that of P2.

Is it usual to get such crystals from similar conditions or am I
missing something?

Many thanks,
Mark

[ccp4bb] double cell dimensions between P2 and C2

[Markus Heckmann]

Dear all,
>From a small protein, gives crystals P2 with cell
Cell 53.16   65.73   72.8990  110.94  90
(has 3 molecules in the asymmetric unit). Tested with pointless. Does
not give any other possibility.

Another crystal if the same protein, similar conditions:
C2
Cell 109.14  124.37   73.4290  111.75  90. This has 6
molecules in the a.s.u. Tested with pointless. Does not give any other
possibility.
The cell length a, b of C2 is twice that of P2.

Is it usual to get such crystals from similar conditions or am I
missing something?

Many thanks,
Mark

[ccp4bb] EM Validation Developer Post

[Ardan Patwardhan]

Dear all

I am looking for a person with a structural biology/bioinformatics background 
and software development experience to work on an exciting joint project with 
Garib Murshudov’s group (MRC-LMB) to develop structural data-mining of 3DEM 
maps in EMDB with the aim of deriving canonical 3D density motifs that can be 
used for validation and analysis.

More details can be found here: 
https://www.embl.de/jobs/searchjobs/index.php?ref=EBI_01074 

and the deadline is: 10 December 2017

Many thanks and best wishes


Ardan Patwardhan
Team Leader - Cellular Structure & 3D Bioimaging
EMDB & EMPIAR
European Bioinformatics Institute (EMBL-EBI) European Molecular Biology 
Laboratory
Wellcome Trust Genome Campus
Hinxton, Cambridge CB10 1SD
Tel: +44 1223 492649