index02 |
Actual MOSFLM input file used to produce the results |
index02.mat |
Input orientation matrix for solution 2, from LABELIT |
index02.out |
MOSFLM screen output |
index02.sum |
MOSFLM summary file |
index02.mtz |
CCP4-formatted integrated spot file |
Most oscillation datasets can be indexed without overriding any
parameters. Indeed, LABELIT has been designed without a graphical user interface
in an effort to create a command-line autoindexing program to work
behind the scenes at synchrotron beamlines. However, there will always be some cases
where the output can be improved if the user carefully inspects the results (see
Graphical Output below) and adjusts certain things in response. In addition to the
autoindex_override items
listed above, here are the other optionally configurable values, listed with their defaults:
beamplot_pdf_file = None This is the most useful parameter which can be set. It is used to create a color contour map showing probable positions of the direct beam on the detector face, as was done for Figure 3d of the LABELIT paper. The most probable candidate beam positions are also ranked and listed. If there are more than 1 highly ranked candidates, LABELIT always autoindexes with each candidate, and chooses the one which gives the lowest rmsd score (observed - predicted) when predicting the diffraction pattern. If there is close contention between different candidate beam centers, the user should use the contour map to judge whether the autoindexing solution can be believed, or if it is necessary to manually experiment with other beam centers (see next paragraph). The name of an output file can be given, e.g., beamplot_pdf_file = '/home/user/public_html/plot.pdf' creates a pdf document in the user's html document directory. |
beam_search_scope = 4.0 Bayesian beam search radius in mm. After examining the probability map above, the user may want to manually select a particular beam candidate. This is useful in rare cases (<2% of the time) where LABELIT's rigorous beam search fails to rank the candidate beam centers in the correct order. To choose a different beam center, use autoindex_override_beam to set the coordinates of the desired beam candidate, and reduce the size of the beam_search_scope, so only one beam candidate is within the radius. The radius must be >= 0.1 mm. LABELIT has not been tested with radius values greater than 4 mm. |
overlapping_spot_criterion = 1.2 As of LABELIT v0.974, it is no longer necessary to fiddle with this parameter. If more than a certain percentage of spots overlap, LABELIT now uses a special procedure to check if the pattern of spots seems like it arises from a large unit cell axis. The spots are accepted for autoindexing. Special MOSFLM keywords are given to adjust for close spots. A check is also run to reject spots that look like they are unresolved aggregates of several Bragg reflections. In versions of LABELIT prior to v0.974, this parameter is useful for judging whether two candidate Bragg spots are too close together to be safely used for autoindexing. Normally the centers of the two spots must be more than 1.2 times the major axis of the largest spot, when the spots are modelled as ellipses. This conservative default becomes problematic for samples with very large unit cells, where the detector has not been pulled back far enough to cleanly separate the spots. If all pairs of close spots have been thrown out, autoindexing will never correctly identify the largest of the three unit cell dimensions. This situation can be detected by carefully looking at the pattern of colored spots in the overlay_distl plot (see Graphical Output below). If close-lying spots are never colored blue or green, it is perfectly reasonable in such cases to set the criterion as low as 0.7 or 0.8. |
distl_lowres_limit = 50.0 Low resolution limit, in Angstroms, used by DISTL when choosing spots for autoindexing. Reasons the user might want to set this to a lower number include: 1) to eliminate artifacts due to scatter off the beamstop; 2) to eliminate extremely bright low-resolution spots from well diffracting crystals such as lysozyme; and 3) to eliminate low resolution diffuse scatter which interferes with autoindexing. Alternatively, the user might need to set this to a higher number to include extremely low resolution spots from crystals with unusually large unit cells. In most cases the default value will work. |
distl_highres_limit = None High resolution limit, in Angstroms, used by DISTL when choosing spots for autoindexing; by default there is no limit. However, in a small percentage of cases the user will notice that at high resolutions Bragg spots seem to form a distorted lattice (this can be seen by inspecting the overlay_distl plot; see Graphical Output below). In such cases, use this parameter to place a limit on spots that are used for autoindexing. |
distl_maximum_number_spots_for_indexing = 300 Even though many hundreds of Bragg spot candidates may be considered "good" for autoindexing, DISTL chooses the brightest 300 by default. In certain images taken from crystals with large unit cells (see overlapping_spot_criterion above), closely spaced spots may not be among the brightest reflections. In extreme cases, the largest unit cell dimension can be missed by the autoindexing procedure. This situation can be recognized by inspecting the overlay_distl plot (see Graphical Output below). If there are closely spaced blue spots (the weaker ones) but no closely spaced green spots (the brightest ones selected for autoindexing), then this parameter must be increased. |
distl_minimum_number_spots_for_indexing = 40 Normally, DISTL requires that each image contain 40 good Bragg spot candidates, or autoindeinxg will be aborted. However, in a small percentage of cases, otherwise well-behaved crystals may have small unit cell dimensions and diffract out only to low resolution, resulting in fewer than 40 spots on an image. This parameter may be decreased in such circumstances. |
lepage_max_delta = 1.4 Angular tolerance in degrees for detecting symmetry elements to list out the candidate Bravais lattices. The user is referred to the LABELIT paper and to LePage J. Appl. Cryst. 15:255(1982) for a full description. The concern here is that if this parameter is too small, potential symmetry may be missed. We have another web site where the user can experiment with different values. The 1.4 degree default has proven to be high enough in all cases examined so far; other parameters such as the beam position are more important for determining correct Bravais symmetry. The user should remember that it is always possible that candidate Bravais symmetry will turn out to be false once the data are integrated and scaled; therefore LABELIT always outputs a list of all possible subgroups. |
rmsd_tolerance = 2.0 For listing subgroups (see paragraph above) this parameter gives the permitted ratio between model rmsd and the triclinic rmsd. For example, if the tetragonal model has rmsd=0.9mm and the triclinic model has rmsd=0.1mm the tetragonal candidate model will not be listed, even if it's LePage delta falls within the permitted range. It is unlikely that the user will be interested in changing this parameter. |
difflimit_sigma_cutoff = 0.75 After MOSFLM integration, the intensities of unmerged fulls and partials are analyzed to determine the resolution limit. The I/sigma cutoff used for this calculation is 0.75 by default. |
distl_profile_bumpiness = 2 When DISTL chooses candidate Bragg spots, this is maximum number of local maxima allowed in a diffraction peak which is to be considered a valid spot. For almost all synchrotron-based datasets, the spot profile is smooth and bell-shaped, so it is fine to filter on 1 or 2 local maxima. However, some images collected on home sources equipped with Nickel mirrors show very detailed structure within the spot profile, requiring this parameter to be set as high as 10. |
A new LABELIT feature. Now there is help. LABELIT versions 1.000wcpcw and higher give a command-line option to input a PBD structure file prior to indexing. Structure factors are calculated, taking the PHENIX bulk solvent correction into account. Labelit 1.1.8/Phenix 1.6.1 and higher also allow the input of observed X-ray intensities or structure factor amplitudes instead of a pdb file.
Integration is done with one or two frames of the raw data, using a preliminary triclinic model. Afterwards, all possible reindexing transformations are considered to produce the best scaling between data and model. This is all done automatically before the final indexing solution is printed out.
Example output. Using the normal indexing procedure, analysis of an example dataset produces the Patterson group with the highest possible symmetry, I 4/mmm, and lists all metrics that are subgroups of I 4/mmm. The actual space group is I 4:
% labelit.index tm1347_mpd_1_###.img 1 90 LABELIT Indexing results: Solution Metric fit rmsd #spots crystal_system unit_cell volume :) 9 0.1804 dg 0.194 460 tetragonal tI 120.18 120.18 144.29 90.00 90.00 90.00 2083945 :) 8 0.1804 dg 0.188 435 orthorhombic oF 144.33 169.80 170.03 90.00 90.00 90.00 4166840 ;( 7 0.1804 dg 0.263 453 monoclinic mC 144.38 169.71 111.50 90.00 130.31 90.00 2083292 :) 6 0.1588 dg 0.148 440 monoclinic mC 144.28 170.05 111.44 90.00 130.26 90.00 2086598 :) 5 0.0857 dg 0.184 459 orthorhombic oI 120.24 120.29 144.18 90.00 90.00 90.00 2085478 ;( 4 0.0857 dg 0.250 466 monoclinic mC 170.18 144.11 120.17 90.00 134.93 90.00 2086454 :) 3 0.0627 dg 0.159 454 monoclinic mC 187.74 120.19 120.44 90.00 129.77 90.00 2088961 :) 2 0.0669 dg 0.170 456 monoclinic mC 187.73 120.23 120.23 90.00 129.80 90.00 2084759 :) 1 0.0000 dg 0.153 440 triclinic aP 111.46 111.56 111.57 99.39 114.61 114.81 1044409 MOSFLM Integration results: Solution SpaceGroup Beam x y distance Resolution Mosaicity RMS :) 9 I4 94.12 99.54 199.94 2.43 0.700000 0.057 1 P1 94.12 99.55 200.02 2.43 0.700000 0.058With the new command line option, eight reindexing possibilities are considered before picking the correct direction of the fourfold. Also, all subsequent processing steps (such as labelit.mosflm_scripts for data integration) will explicitly use the provided space group, I4. Only three space groups are printed in the output, I4 and its two proper subgroups:
% labelit.index tm1347_mpd_1_###.img 1 90 compatibility_file=1vrd.pdb LABELIT Indexing results: Comparing observed data (Frames 1, 90)... to reference model 1vrd.pdb There are 8 reindexing choices with compatible cells, of which 4 cluster around the lowest Rscale Best overall Rscale factor is 30.06% out to resolution 3.70 Angstroms Solution Metric fit rmsd #spots space_group unit_cell volume :) 3 0.1804 dg 0.187 463 tI I 4 120.19 120.19 144.32 90.00 90.00 90.00 2084927 :) 2 0.0857 dg 0.255 460 mC C 1 2 1 169.84 144.33 120.07 90.00 134.91 90.00 2084708 :) 1 0.0000 dg 0.292 446 aP P 1 111.57 111.62 111.46 99.37 114.61 114.87 1044409 MOSFLM Integration results: Solution SpaceGroup Beam x y distance Resolution Mosaicity RMS :) 3 I4 94.12 99.54 199.96 2.43 0.700000 0.053 1 P1 94.12 99.55 200.02 2.43 0.700000 0.058Note: as presently implemented, the compatible indexing algorithm requires back-to-back images when comparing raw data to input model. In the above example, indexing is requested on frames 1 and 90, so the comparison algorithm actually requires frames 1,2,90 and 91 to be present on disk. An error message is generated if frames 2 and 91 are not present.
Input of a structure factor file:
% labelit.index tm1347_mpd_1_###.img 1 90 compatibility_file=truncated.mtz [compatibility_column_label=label] % # column labels IMEAN I F are OK by default, without specifying the label.
Usage:
labelit.index [first wedge dataset] labelit.store_crystal_orientation labelit.index [second wedge dataset, to be aligned with the first>] labelit.reset # erases the alignment matrix
Example output. We consider two possible scenarios. The first involves a single triclinic crystal used for PDB entry 2rh0 (Joint Center for Structural Genomics), which has pseudo-mC metric symmetry.
% labelit.index 2rh0/data/jcsg/aps3/GMCA_23ID_D/20070819/collection/13542905/58046/58046_1.#### 1 90 LABELIT Indexing results: Beam center x 145.06mm, y 148.58mm, distance 250.04mm ; 80% mosaicity=0.80 deg. Solution Metric fit rmsd #spots crystal_system unit_cell volume :) 2 0.2494 dg 0.314 328 monoclinic mC 101.77 77.56 44.23 90.00 101.01 90.00 342734 :) 1 0.0000 dg 0.394 379 triclinic aP 44.26 63.81 64.04 74.62 81.31 81.19 171168 % labelit.store_crystal_orientation % labelit.index 2rh0/data/jcsg/aps3/GMCA_23ID_D/20070819/collection/13542905/58046/58046_2.#### 1 90 Based on stored crystal orientation, reindexing a',b',c' = -a,-c,-b New dataset shifted 0.00 degrees around the rotation axis with respect to the stored orientation LABELIT Indexing results: Beam center x 145.10mm, y 148.62mm, distance 249.88mm ; 80% mosaicity=0.90 deg. Solution Metric fit rmsd #spots crystal_system unit_cell volume :) 2 0.0951 dg 0.292 427 monoclinic mC 102.05 77.60 44.21 90.00 100.87 90.00 343808 :) 1 0.0000 dg 0.386 438 triclinic aP 44.21 64.17 64.07 74.50 81.37 81.36 171978...Notice that the second dataset has a non-standard setting, which nonetheless is aligned with the first indexing solution. The small differences in the cell dimensions between the two datasets are attributable to experimental uncertainty in the cell measurement.
Note the statement that the new dataset is shifted "0.00" degrees around the rotation axis. This indicates that the orientation is known very precisely (because two images are used for indexing, related by a 90-degree rotation). But the second dataset can still be aligned even if the orientation is less-precisely known. For example, if only one oscillation image is used for indexing, it is not uncommon to see the second dataset shifted as much as +/- 1.0 degrees from the first dataset.
Our second scenario involves a synchrotron beamline with a robot automounter. The crystal is mounted once, two images are acquired, the crystal is placed back in the storage Dewar, and finally is remounted again at a later time. The goniometer is set to the same position for each crystal mounting, but the mounting pin has slipped the second time with respect to the first trial. A different algorithm is used for aligning the orientation matrices; this time we try each possible reindexing transformation, and at the same time allow a free rotation around the axis (usually phi). It is not possible to know the alignment with certainty (consider, for example, if a tetragonal crystal has its c axis aligned perfectly with phi giving four possible positions). However, if the crystal is randomly orientated, then usually there is only one solution possible, and this is reported as follows:
% labelit.index 1vrd/data/jcsg/als1/5.0.3/20011020/TM1347/T3879/tm1347_mpd_1_###.img 1 301 LABELIT Indexing results: Beam center x 94.14mm, y 99.27mm, distance 199.97mm ; 80% mosaicity=1.10 deg. Solution Metric fit rmsd #spots crystal_system unit_cell volume :) 9 0.1420 dg 0.141 508 tetragonal tI 120.39 120.39 144.32 90.00 90.00 90.00 2091740 :) 8 0.1390 dg 0.141 508 orthorhombic oI 120.40 120.38 144.32 90.00 90.00 90.00 2091745 :) 7 0.1420 dg 0.154 514 orthorhombic oF 144.33 170.24 170.26 90.00 90.00 90.00 4183629 :) 6 0.1390 dg 0.190 507 monoclinic mC 170.25 144.33 120.39 90.00 135.00 90.00 2091817 :) 5 0.1420 dg 0.122 502 monoclinic mC 144.23 170.30 111.41 90.00 130.20 90.00 2090137 :) 4 0.1184 dg 0.132 507 monoclinic mC 187.86 120.40 120.41 90.00 129.77 90.00 2093408 :) 3 0.0905 dg 0.240 522 monoclinic mC 187.68 120.45 120.36 90.00 129.79 90.00 2090832 :) 2 0.0417 dg 0.188 507 monoclinic mC 144.36 170.23 111.54 90.00 130.23 90.00 2092834 :) 1 0.0000 dg 0.145 494 triclinic aP 111.52 111.59 111.63 99.39 114.71 114.65 1046659 % labelit.store_crystal_orientation % labelit.index 1vrd/data/jcsg/als1/5.0.3/20011020/TM1347/T3879/tm1347_mpd_1_###.img 2 302 Based on stored crystal orientation, reindexing a',b',c' = -b,-a,-c New dataset matches the known orientation with a -4.88 degree slip around the rotation axis. This is a possible outcome if the crystal has been remounted (see LABELIT documentation). LABELIT Indexing results: Beam center x 94.15mm, y 99.29mm, distance 199.94mm ; 80% mosaicity=1.20 deg. Solution Metric fit rmsd #spots crystal_system unit_cell volume :) 9 0.0632 dg 0.155 505 tetragonal tI 120.41 120.41 144.19 90.00 90.00 90.00 2090412 :) 8 0.0632 dg 0.154 503 orthorhombic oI 120.40 120.41 144.18 90.00 90.00 90.00 2090312 :) 7 0.0563 dg 0.155 507 orthorhombic oF 144.25 170.21 170.29 90.00 90.00 90.00 4181375 :) 6 0.0562 dg 0.197 505 monoclinic mC 187.83 120.42 120.40 90.00 129.86 90.00 2090506 :) 5 0.0632 dg 0.215 509 monoclinic mC 187.76 120.40 120.40 90.00 129.84 90.00 2089772 :) 4 0.0546 dg 0.185 502 monoclinic mC 170.22 144.24 120.39 90.00 134.99 90.00 2090543 :) 3 0.0563 dg 0.188 501 monoclinic mC 144.25 170.21 111.58 90.00 130.26 90.00 2090585 :) 2 0.0175 dg 0.125 496 monoclinic mC 144.18 170.31 111.44 90.00 130.23 90.00 2089360 :) 1 0.0000 dg 0.153 495 triclinic aP 111.56 111.47 111.57 99.46 114.71 114.65 1044661It is not necessary to specify at the command line which scenario applies. If no alignment is found with the first scenario, then the search is automatically repeated allowing for slippage around the phi axis.
This can go on the command line, or the dataset_preferences.py file!
Having done that, the key trick for your dataset is to notice that the spots on the 500A c-axis aren't really separated
down to the baseline (as you mentioned), leading spotfinder to reject all spots that are closely spaced on a c-axis line. The solution is to raise the bar as to what spotfinder considers to be an acceptable
baseline. By default the cut off is 1.5 sigma (CCDs) or 2.5 sigma (Pilatus), where sigma is the rmsd deviation of local pixels away
from the best-fit background plane. If the cutoff is changed to 5.0, your pattern can
be indexed. On the command line:
distl.minimum_signal_height=5.0
...this raises the background cutoff.
In rare cases, two images may not be enough to completely sample the lattice. The user can specify more than two images on the command line, but LABELIT must be instructed to accept this input by the placment of a keyword on the command line or in the dataset_preferences.py file:
wedgelimit = [maximum_permissible_number_of_images] By default, the maximum permissible number of images that can be specified on the command line is two. |
The wedgelimit keyword should not be necessary in most cases. If a clear example is found requiring more than two images for indexing, this should be brought to the attention of the program authors.
LABELIT intentionally prohibits the use of images that are back-to-back in rotation angle, such as a 0-to-1 and a 1-to-2 degree image. This is because the program does not have any algorithm to distinguish between the same Bragg spot partially recorded on consecutive images, versus two different Bragg spots from adjacent lattice positions. Generally things work fine with this restriction. Possible exceptions might include data sets that are finely sliced in phi. In some such datasets, there may not be sufficient numbers of Bragg spots on each image for indexing. Such datasets should be brought to the attention of the program authors for further investigation.
LABELIT Indexing results: Beam center x 162.65mm, y 162.38mm, distance 299.94mm ; 80% mosaicity=0.70 deg. Solution Metric fit rmsd #spots crystal_system unit_cell volume xx 9 0.8778 dg 0.238 137 tetragonal tP 83.28 83.28 81.36 90.00 90.00 90.00 564268 xx 8 0.8778 dg 0.243 135 orthorhombic oC 117.75 117.87 81.37 90.00 90.00 90.00 1129382 xx 7 0.8778 dg 0.241 135 monoclinic mC 117.75 117.86 81.34 90.00 89.98 90.00 1128850 xx 6 0.8770 dg 0.241 136 monoclinic mC 117.86 117.75 81.33 90.00 89.96 90.00 1128741 :) 5 0.0730 dg 0.105 137 orthorhombic oP 81.27 82.65 83.91 90.00 90.00 90.00 563641 :) 4 0.0730 dg 0.105 135 monoclinic mP 81.27 82.64 83.91 90.00 89.98 90.00 563528 :) 3 0.0488 dg 0.098 136 monoclinic mP 82.64 81.27 83.94 90.00 89.94 90.00 563776 :) 2 0.0587 dg 0.094 133 monoclinic mP 81.28 83.91 82.65 90.00 89.95 90.00 563745 :) 1 0.0000 dg 0.092 133 triclinic aP 81.29 82.65 83.92 89.94 89.98 89.95 563827 MOSFLM Integration results: Solution SpaceGroup Beam x y distance Resolution Mosaicity RMS :) 5 P222 162.73 162.76 300.36 3.41 0.700000 0.201 1 P1 162.71 162.75 300.48 3.42 0.700000 0.194Answer: The Bravais lattice solutions are classified either as likely ":)", unlikely ":(", or very unlikely "xx". The critical thing to understand is that lattice symmetry is not measured, it is an abstract constraint that is imposed, if the unit cell measurements and integrated intensities fall within a close enough tolerance. For labelit.index we do not have reduced intensities yet; the output table presents best guesses based solely on Bragg spot positions. Previously, the "very unlikely" lattice settings were not printed at all; these are defined as settings for which
rmsd(setting) > rmsd_tolerance * rmsd(triclinic)where rmsd (in mm) is root-mean-squared-deviation (observed vs. predicted position) of well-fitting spots, and rmsd_tolerance is a parameter that can be defined on the command line or in the "dataset_preferences.py" file (default=3.5; prior to Nov 2010 the default was 2.0). It was reluctantly realized that no single cutoff value could adequately decide the true lattice symmetry in all cases, thus it was decided to print the "very unlikely" lattice settings along with the others. In the case shown, it is likely that the lattice is orthorhombic (oP), but a tetragonal solution cannot be ruled out at this stage. Indeed, it is possible to impose cubic symmetry by distorting the observed lattice by 1.83 degrees. This can be discovered with the command
iotbx.lattice_symmetry --unit-cell=81.29,82.65,83.92,89.94,89.98,89.95 PHowever, from experience with macromolecular indexing, no observed lattice is ever distorted from the true geometry by more than 1.4 degrees. Therefore, for printing out the table we impose a strict limit on the metric fit:
Metric fit (degrees) < lepage_max_deltawhere lepage_max_delta is another "dataset_preferences.py" parameter, 1.4 degrees by default.
Filing a bug report: labelit.bugreporter
If autoindexing fails and there is a suspicion that there may be a program
bug, a detailed bug report can be prepared and emailed to the program authors.
This command has the same syntax as labelit.index, so for example
labelit.bugreporter /home/data 1 90 will try to index frames 1 and 90 in
the directory /home/data. A printout detailing every line of executed
python code will be redirected to the file bugreport. This very large
file (typically tens of megabytes) can be gzip'ed and mailed to the developers.
Requirements: LABELIT installation CCP4 MOSFLM (aliased to "ipmosflm") SCALA REINDEX Synopsis: The user collects a dataset, or a partial dataset. The diffraction pattern is indexed, and data are integrated assuming a P1 spacegroup. The integrated Bragg spots are then analyzed under all Patterson symmetries to find the highest symmetry consistent with the data. To avoid deducing the wrong symmetry under some circumstances, we use the Rsymop statistic (Sauter, Grosse-Kunstleve & Adams [2006], J. Appl. Cryst., 39, 158-168) instead of the traditional Rmerge. Finally, systematic extinctions are inspected to determine if screw axes can be found. Primer: As with other labelit commands, a current working directory should be set up which may or may not contain the detector data. To index the diffraction pattern use a command like this: labelit.index /net/adder/raid1/sauter/rawdata/alpha_lytic/ 1 91 This syntax asks labelit to look in the directory /net/adder/raid1/sauter/rawdata/alpha_lytic/ for any diffraction images with image numbers 1 and 91, and use these to index the diffraction pattern. It is generally recommended to use frames 90-degrees apart. FOR SYNCHROTRON DEVELOPERS, it would make sense for the data collection controls to have a default where the 90-to-91 degree image is collected first, e.g., in file alpha_lytic_1_091.img, and then revert back to phi=0 to start collecting image number 1. Next, a script is called to determine the spacegroup: labelit.rsymop 1 24 This syntax assumes that the previously determined indexing solution is to be used as a starting point, but that frames will only be integrated from nubmers 1 to 24. This allows symmetry to be determined while the data are still being acquired, and it should take on the order of 2 minutes. The following steps are performed by labelit.rsymop: 1. An attempt is made to postrefine the indexing solution using MOSFLM. This is done in the triclinic setting since at this point the spacegroup is not known. However, with the lack of higher symmetry it is difficult to postrefine, particularly if the angular wedge is much smaller than 90 degrees. Therefore the following provisions are made: Postrefinement is attempted using two 3-degree data wedges (containing at least 3 frames each). If the dataset contains more than 93 degrees of rotation then wedges are chosen 90 degrees apart; otherwise, data are chosen from the beginning and end of the oscillation range. If there are insufficient frames or degrees of data, the LABELIT model is used without further refinement. Also, if the model diverges more than 2% away from its starting point, we again revert to the LABELIT model. 2. MOSFLM is used to integrate the partial dataset, assuming a triclinic setting. For integration, the high-resolution cutoff is set to a value beyond the expected resolution limit of the data, so that weak reflections can be properly included. Then a new analysis of the resolution cutoff is performed based on the integrated intensities, so that scaling can be done with a conservative cutoff of 5-sigma. The 5-sigma cutoff is determined on resolution bins combining partials and fulls. 3. The data are scaled with the program SCALA in the highest-possible Patterson group consistent with the unit cell dimensions (the "metric supergroup"). For the example given below this is P 6/m m m. The data are not merged after scaling. The Rsymop statistics are then calculated (Sauter, submitted). Also, presumptive Rmerge statistics are calculated for each possible Patterson group ("presumptive" means that we presume to calculate merging statistics for a subgroup even though the data are scaled in the supergroup. This is usually a justified). The presumptive Rmerge is listed in the "Rmp" column in the example below. 4. The likeliest Patterson group is chosen. The data are rescaled and merged in this group, and then the merged intensities are checked for systematic absences to indicate screw axes. A typical final output is shown here: Symmetry Operator Nobs Rsymop x,y,z 3520 3.0% -x,-x+y,-z 1158 3.1% y,x,-z 30214 3.3% -x+y,-x,z 2288 3.5% -y,x-y,z 2288 3.5% x-y,-y,-z 5116 3.9% x-y,x,z 2541 46.6% y,-x+y,z 2541 46.6% x,x-y,-z 2588 47.6% -x+y,y,-z 3998 48.6% -y,-x,-z 31860 50.0% -x,-y,z 33744 50.7% Soln Patterson Operators_in_group max(Rsymop) Rmp SpaceGroups 12 P -3 S..SS....... 3.5% 3.1% P3 P31 P32 12 P -3 m 1 SSSSSS...... 3.9% 3.5% ;(P321 :)P3121 :)P3221 12 P -3 1 m S..SS...SSS. 50.0% 42.4% 12 P 6/m S..SS.SS...S 50.7% 45.5% 12 P 6/m m m SSSSSSSSSSSS 50.7% 44.1% 11 C m m m S.S.......SS 50.7% 44.1% 10 C 1 2/m 1 S.S......... 3.3% 3.5% C121 09 C m m m SS......S..S 50.7% 47.8% 08 C 1 2/m 1 S.......S... 47.6% 10.7% 07 C m m m S....S...S.S 50.7% 46.4% 06 P 1 2/m 1 S..........S 50.7% 48.5% 05 C 1 2/m 1 SS.......... 3.1% 3.0% C121 04 C 1 2/m 1 S........S.. 48.6% 10.6% 03 C 1 2/m 1 S.........S. 50.0% 43.3% 02 C 1 2/m 1 S....S...... 3.9% 3.2% C121 01 P -1 S........... 3.0% 3.0% P1 The Solution numbers correspond to those Bravais groups previously identified by LABELIT. Note in this example that for the hexagonal-primitive Bravais setting (solution 12), there are 5 possible Patterson symmetries. The "Operators_in_group" column shows which symmetry operators are present in a particular subgroup. For example, the P -3 subgroup has operators #1,#4 & #5 that are listed in the upper table. These three operators have Rsymop values of 3.0%, 3.5% and 3.5%, so "3.5%" is listed in the "max(Rsymop)" column. Subgroups with a reasonably low max(Rsymop) are considered to be potential Patterson symmetries, and these are annotated under the "SpaceGroups" column, where all possible enantiomorphic space groups are listed. Furthermore, it is reasonable to conclude that the true Patterson symmetry is the highest symmetry consistent with the data. Here, the "P -3 m 1" symmetry is the highest group with a reasonable max(Rsymop), and therefore the 3 spacegroups P321, P3121, and P3221 have flag-notations next to them. The SCALA output is scanned to determine if enough systematic absences have been detected to make definitive conclusions about screw axes. In this particular case, it is possible to conclude that the space group is either P3121 or P3221 --thus the smiley face :)-- and not P321, thus the frowning face ;(. Note that it is not possible to choose between P3121 and P3221 until a molecular model is fit to the electron density. A list of all possible Patterson symmetries, along with space groups and corresponding systematic extinctions can be printed with the command labelit.rsymop --reference Note that in some cases, the crucial axis for determining systematic absences may lie near the spindle, and therefore these data will be missing from the current partial dataset. Indeed, it may be the case that no amount of phi rotation will bring this axis into the sphere of reflection; it may be necessary to re-orient the crystal using a different camera axis. If axial data are missing, it will not be possible to distinguish whether the crystal symmetry contains a screw axis. In cases such as this, all space groups that are still consistent with the partial dataset are indicated by question marks as follows: ??P121 ??P1211 This means that the true space group is either P2 or P21. In cases where only a few frames are scaled, there may be insufficient angular coverage to calculate an Rsymop for a particular symmetry operator. It is possible to know this by looking for Nobs values <5, in which case the Rsymop will be listed as "0.0%". Under the "Operators_in_group" column, operators with too few observations are listed with lower case "s". The rsymop command takes several minutes to execute. The final output table is printed to the screen, not to a file. To regenerate this table again a second time (using the output files from the previously run job) one can issue the command labelit.stats_rsymop Note that all results from indexing and space group determination can be permanently deleted from the directory by typing labelit.reset
rsymop_integration_permissible_resolution = None Before calculating Rsymop statistics, the dataset is postrefined and integrated with MOSFLM. The outer resolution cutoff used for this step is normally the outer resolution determined by labelit.index (defined as the resolution shell where the average I/sigma ratio for all fulls and partials drops to 0.75). If the user wishes to limit the Rsymop command to a lower resolution, then the rsymop_integration_permissible_resolution can be specified in Angstroms. |
rsymop_statistics_sigma_cutoff = 5.0 As described above, a resolution cutoff is applied prior to scaling and determining the Rsymop statistics. Resolution shells are thrown out where the average I/sigma ratio drops below 5.0. The rsymop_statistics_sigma_cutoff parameter overrides this value. |