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== Preparation ==
== Preparation ==


From visual inspection (using [[ADXV]]) we realize that the first frame of each dataset looks good (diffraction to 2 A), the last bad (10 A), and there is an obvious degradation from each frame to the next.   
From visual inspection (using [[adxv]]) we realize that the first frame of each dataset looks good (diffraction to 2 A), the last bad (10 A), and there is an obvious degradation from each frame to the next.   


We have to get some idea about possible spacegroups first. This means processing some of the datasets. Let's choose "xtal100", the last one.
We have to get some idea about possible spacegroups first. This means processing some of the datasets. Let's choose "xtal100", the last one.


  generate_XDS.INP "../../Illuin/microfocus/xtal100_1_001.img"
  generate_XDS.INP "../../Illuin/microfocus/xtal100_1_0??.img"


To maximize the number of reflections that should be used for spacegroup determination, the only changes to XDS.INP are:
To maximize the number of reflections that should be used for spacegroup determination, the only changes to XDS.INP are:
  TEST_RESOLUTION_RANGE= 50 0 ! default is 10 4  
  TEST_RESOLUTION_RANGE= 50 0 ! default is 10 4 ; we want all reflections instead
  DATA_RANGE= 1 1            ! R-factors involving more than 1 frame are meaningless  
  DATA_RANGE= 1 1            ! R-factors involving more than 1 frame are meaningless  
                             ! with such strong radiation damage
                             ! with such strong radiation damage


We run "xds" and, after a few seconds, can inspect IDXREF.LP and CORRECT.LP. It turns out the primitve cell is 38.3, 79.2, 79.2, 90, 90, 90 which is compatible with tetragonal spacegroups, or those with lower symmetry:
We run "xds" and, after a few seconds, can inspect IDXREF.LP and CORRECT.LP. It turns out that the primitve cell is 38.3, 79.2, 79.2, 90, 90, 90 which is compatible with tetragonal spacegroups, or those with lower symmetry:


   LATTICE-  BRAVAIS-  QUALITY  UNIT CELL CONSTANTS (ANGSTROEM & DEGREES)    REINDEXING TRANSFORMATION
   LATTICE-  BRAVAIS-  QUALITY  UNIT CELL CONSTANTS (ANGSTROEM & DEGREES)    REINDEXING TRANSFORMATION
Line 74: Line 74:
== devising a bootstrap procedure ==
== devising a bootstrap procedure ==


We have to realize that, since the b and c axes are equal, we can index each dataset in two non-equivalent ways. This is the same situation as would occur e.g. for spacegroups P3(x) and P4(x), and means that we'll have to use a REFERENCE_DATA_SET to
We have to realize that, since the b and c axes are equal, we can index each dataset in two non-equivalent ways. This is the same situation as occurs e.g. for spacegroups P3(x) and P4(x), and means that we'll have to use a REFERENCE_DATA_SET to get the right setting for each of the 100 datasets.
 
However, we cannot expect that all of the datasets have enough reflections in common with a given dataset. Thus, we have to update and enlarge the REFERENCE_DATA_SET after the first round, using those datasets that have reflections in common with the old REFERENCE_DATA_SET. Then in a second round, we can hopefully identify the correct setting for all datasets. After that, we can scale everything together.
 
== first round of bootstrap ==
 
We choose xtal100 as the first reference, and move its XDS_ASCII.HKL to bootstrap/reference.ahkl. A script that goes through all datasets, produces XDS.INP, and runs xds is the following (note that we only REFINE(IDXREF)= ORIENTATION BEAM , and the same for REFINE(INTEGRATE), since it may be useful to keep the b and c axis exactly the same):
 
<pre>
#!/bin/csh -f
foreach f ( Illuin/microfocus/xtal*_1_001.img )
setenv x `echo $f | cut -c 19-25`
echo processing $x
rm -rf bootstrap/$x
mkdir bootstrap/$x
cd bootstrap/$x
cat>XDS.INP<<EOF
JOB= XYCORR INIT COLSPOT IDXREF DEFPIX INTEGRATE CORRECT
ORGX= 1511.2 ORGY= 1553.1 ! ORGX=1507 ORGY=1570 if BEAM is not refined
DETECTOR_DISTANCE= 250
OSCILLATION_RANGE= 1
X-RAY_WAVELENGTH= 0.979338
NAME_TEMPLATE_OF_DATA_FRAMES=../../Illuin/microfocus/${x}_1_0??.img
DATA_RANGE=1 1
SPOT_RANGE=1 1
REFERENCE_DATA_SET=../reference.ahkl
TEST_RESOLUTION_RANGE= 50.0 2.0 ! for correlating with reference
SPACE_GROUP_NUMBER=16                  ! 0 if unknown
UNIT_CELL_CONSTANTS= 38.3 79.1 79.1  90 90 90 ! mean of CORRECT outputs
INCLUDE_RESOLUTION_RANGE=60 1.8  ! after CORRECT, insert high resol limit; re-run CORRECT
TRUSTED_REGION=0.00 1.  ! partially use corners of detectors; 1.41421=full use
VALUE_RANGE_FOR_TRUSTED_DETECTOR_PIXELS=7000. 30000. ! often 8000 is ok
MINIMUM_ZETA=0.05        ! integrate close to the Lorentz zone; 0.15 is default
STRONG_PIXEL=5         
MINIMUM_NUMBER_OF_PIXELS_IN_A_SPOT=3 ! default of 6 is sometimes too high
REFINE(INTEGRATE)=  ORIENTATION BEAM ! AXIS DISTANCE CELL
REFINE(IDXREF)= ORIENTATION BEAM ! AXIS DISTANCE CELL
! parameters specifically for this detector and beamline:
DETECTOR= ADSC MINIMUM_VALID_PIXEL_VALUE= 1 OVERLOAD= 65000
NX= 3072 NY= 3072  QX= 0.102539  QY= 0.102539 ! to make CORRECT happy if frames are unavailable
DIRECTION_OF_DETECTOR_X-AXIS=1 0 0
DIRECTION_OF_DETECTOR_Y-AXIS=0 1 0
INCIDENT_BEAM_DIRECTION=0 0 1 ! 0.00203 -0.0065 1.02107 ! mean of CORRECT outputs
ROTATION_AXIS=1 0 0    ! at e.g. SERCAT ID-22 this needs to be -1 0 0
FRACTION_OF_POLARIZATION=0.98  ! better value is provided by beamline staff!
POLARIZATION_PLANE_NORMAL=0 1 0
EOF
xds >& xds.log &
sleep 1
  cd ../..
end
</pre>
 
Running this script takes 2 minutes. After this, it's a good idea to check whether the cell parameters are really what we assumed they are:
 
grep UNIT_CELL_CO xtal0[01]*/XDS_ASCII.HKL | cut -c24- > CELLPARM.INP
cellparm
cat CELLPARM.LP
and obtain:
        A        B        C      ALPHA    BETA      GAMMA    WEIGHT
    38.311    79.096    79.107    90.000    90.000    90.000      1.0
    38.292    79.081    79.078    90.000    90.000    90.000      1.0
    38.285    79.021    79.048    90.000    90.000    90.000      1.0
    38.308    79.106    79.099    90.000    90.000    90.000      1.0
    38.298    79.096    79.084    90.000    90.000    90.000      1.0
    38.310    79.117    79.109    90.000    90.000    90.000      1.0
    38.317    79.120    79.124    90.000    90.000    90.000      1.0
    38.302    79.102    79.097    90.000    90.000    90.000      1.0
    38.309    79.119    79.134    90.000    90.000    90.000      1.0
    38.288    79.098    79.128    90.000    90.000    90.000      1.0
    38.294    79.102    79.119    90.000    90.000    90.000      1.0
    38.299    79.104    79.100    90.000    90.000    90.000      1.0
    38.296    79.113    79.058    90.000    90.000    90.000      1.0
    38.322    79.091    79.120    90.000    90.000    90.000      1.0
    38.284    79.082    79.094    90.000    90.000    90.000      1.0
    38.284    79.103    79.098    90.000    90.000    90.000      1.0
    38.303    79.109    79.111    90.000    90.000    90.000      1.0
    38.293    79.084    79.083    90.000    90.000    90.000      1.0
    38.300    79.095    79.101    90.000    90.000    90.000      1.0
------------------------------------------------------------------------
    38.300    79.097    79.100    90.000    90.000    90.000      19.0
 
Why not use all datasets? The reason is that cellparm has a limit of 20 datasets! But it seems to confirm that the cell axes are really 38.3, 79.1, 79.1.
 
Now we run xscale with the following XSCALE.INP :
 
<pre>
OUTPUT_FILE=temp.ahkl
 
INPUT_FILE=../xtal001/XDS_ASCII.HKL
INPUT_FILE=../xtal002/XDS_ASCII.HKL
INPUT_FILE=../xtal003/XDS_ASCII.HKL
INPUT_FILE=../xtal004/XDS_ASCII.HKL
INPUT_FILE=../xtal005/XDS_ASCII.HKL
INPUT_FILE=../xtal006/XDS_ASCII.HKL
INPUT_FILE=../xtal007/XDS_ASCII.HKL
INPUT_FILE=../xtal008/XDS_ASCII.HKL
INPUT_FILE=../xtal009/XDS_ASCII.HKL
INPUT_FILE=../xtal010/XDS_ASCII.HKL
INPUT_FILE=../xtal011/XDS_ASCII.HKL
INPUT_FILE=../xtal012/XDS_ASCII.HKL
INPUT_FILE=../xtal013/XDS_ASCII.HKL
INPUT_FILE=../xtal014/XDS_ASCII.HKL
INPUT_FILE=../xtal015/XDS_ASCII.HKL
INPUT_FILE=../xtal016/XDS_ASCII.HKL
INPUT_FILE=../xtal017/XDS_ASCII.HKL
INPUT_FILE=../xtal018/XDS_ASCII.HKL
INPUT_FILE=../xtal019/XDS_ASCII.HKL
INPUT_FILE=../xtal020/XDS_ASCII.HKL
INPUT_FILE=../xtal021/XDS_ASCII.HKL
INPUT_FILE=../xtal022/XDS_ASCII.HKL
INPUT_FILE=../xtal023/XDS_ASCII.HKL
INPUT_FILE=../xtal024/XDS_ASCII.HKL
INPUT_FILE=../xtal025/XDS_ASCII.HKL
INPUT_FILE=../xtal026/XDS_ASCII.HKL
INPUT_FILE=../xtal027/XDS_ASCII.HKL
INPUT_FILE=../xtal028/XDS_ASCII.HKL
INPUT_FILE=../xtal029/XDS_ASCII.HKL
INPUT_FILE=../xtal030/XDS_ASCII.HKL
INPUT_FILE=../xtal031/XDS_ASCII.HKL
INPUT_FILE=../xtal032/XDS_ASCII.HKL
INPUT_FILE=../xtal033/XDS_ASCII.HKL
INPUT_FILE=../xtal034/XDS_ASCII.HKL
INPUT_FILE=../xtal035/XDS_ASCII.HKL
INPUT_FILE=../xtal036/XDS_ASCII.HKL
INPUT_FILE=../xtal037/XDS_ASCII.HKL
INPUT_FILE=../xtal038/XDS_ASCII.HKL
INPUT_FILE=../xtal039/XDS_ASCII.HKL
INPUT_FILE=../xtal040/XDS_ASCII.HKL
INPUT_FILE=../xtal041/XDS_ASCII.HKL
INPUT_FILE=../xtal042/XDS_ASCII.HKL
INPUT_FILE=../xtal043/XDS_ASCII.HKL
INPUT_FILE=../xtal044/XDS_ASCII.HKL
INPUT_FILE=../xtal045/XDS_ASCII.HKL
INPUT_FILE=../xtal046/XDS_ASCII.HKL
INPUT_FILE=../xtal047/XDS_ASCII.HKL
INPUT_FILE=../xtal048/XDS_ASCII.HKL
INPUT_FILE=../xtal049/XDS_ASCII.HKL
INPUT_FILE=../xtal050/XDS_ASCII.HKL
INPUT_FILE=../xtal051/XDS_ASCII.HKL
INPUT_FILE=../xtal052/XDS_ASCII.HKL
INPUT_FILE=../xtal053/XDS_ASCII.HKL
INPUT_FILE=../xtal054/XDS_ASCII.HKL
INPUT_FILE=../xtal055/XDS_ASCII.HKL
INPUT_FILE=../xtal056/XDS_ASCII.HKL
INPUT_FILE=../xtal057/XDS_ASCII.HKL
INPUT_FILE=../xtal058/XDS_ASCII.HKL
INPUT_FILE=../xtal059/XDS_ASCII.HKL
INPUT_FILE=../xtal060/XDS_ASCII.HKL
INPUT_FILE=../xtal061/XDS_ASCII.HKL
INPUT_FILE=../xtal062/XDS_ASCII.HKL
INPUT_FILE=../xtal063/XDS_ASCII.HKL
INPUT_FILE=../xtal064/XDS_ASCII.HKL
INPUT_FILE=../xtal065/XDS_ASCII.HKL
INPUT_FILE=../xtal066/XDS_ASCII.HKL
INPUT_FILE=../xtal067/XDS_ASCII.HKL
INPUT_FILE=../xtal068/XDS_ASCII.HKL
INPUT_FILE=../xtal069/XDS_ASCII.HKL
INPUT_FILE=../xtal070/XDS_ASCII.HKL
INPUT_FILE=../xtal071/XDS_ASCII.HKL
INPUT_FILE=../xtal072/XDS_ASCII.HKL
INPUT_FILE=../xtal073/XDS_ASCII.HKL
INPUT_FILE=../xtal074/XDS_ASCII.HKL
INPUT_FILE=../xtal075/XDS_ASCII.HKL
INPUT_FILE=../xtal076/XDS_ASCII.HKL
INPUT_FILE=../xtal077/XDS_ASCII.HKL
INPUT_FILE=../xtal078/XDS_ASCII.HKL
INPUT_FILE=../xtal079/XDS_ASCII.HKL
INPUT_FILE=../xtal080/XDS_ASCII.HKL
INPUT_FILE=../xtal081/XDS_ASCII.HKL
INPUT_FILE=../xtal082/XDS_ASCII.HKL
INPUT_FILE=../xtal083/XDS_ASCII.HKL
INPUT_FILE=../xtal084/XDS_ASCII.HKL
INPUT_FILE=../xtal085/XDS_ASCII.HKL
INPUT_FILE=../xtal086/XDS_ASCII.HKL
INPUT_FILE=../xtal087/XDS_ASCII.HKL
INPUT_FILE=../xtal088/XDS_ASCII.HKL
INPUT_FILE=../xtal089/XDS_ASCII.HKL
INPUT_FILE=../xtal090/XDS_ASCII.HKL
INPUT_FILE=../xtal091/XDS_ASCII.HKL
INPUT_FILE=../xtal092/XDS_ASCII.HKL
INPUT_FILE=../xtal093/XDS_ASCII.HKL
INPUT_FILE=../xtal094/XDS_ASCII.HKL
INPUT_FILE=../xtal095/XDS_ASCII.HKL
INPUT_FILE=../xtal096/XDS_ASCII.HKL
INPUT_FILE=../xtal097/XDS_ASCII.HKL
INPUT_FILE=../xtal098/XDS_ASCII.HKL
INPUT_FILE=../xtal099/XDS_ASCII.HKL
INPUT_FILE=../xtal100/XDS_ASCII.HKL
</pre>
 
xscale writes XSCALE.LP which has the 5050 correlation coefficients of every dataset with every other dataset! The order of listing of the correlation coefficients is such that it turns out that is was a good choice to have xtal100 as the REFERENCE_DATA_SET, because we find this list:
 
      CORRELATIONS BETWEEN INPUT DATA SETS AFTER CORRECTIONS
DATA SETS  NUMBER OF COMMON  CORRELATION  RATIO OF COMMON  B-FACTOR
  #i  #j    REFLECTIONS    BETWEEN i,j  INTENSITIES (i/j)  BETWEEN i,j
with these final 99 lines:
    1  100          12          0.601            0.8200        0.0085
    2  100          24          0.998            0.9001        0.5637
    3  100          16          0.990            0.9216        -0.2983
    4  100          16          0.239            1.9141        -0.2253
    5  100          31          0.996            0.9231        0.3755
    6  100          22          0.997            0.9412        0.2726
    7  100          11          0.976            0.8848        -0.1225
    8  100          5          0.967            0.9166        0.0435
    9  100          34          0.160            1.2885        0.0774
  10  100          11          0.860            2.9740        -0.2614
  11  100          8          0.997            0.8732        0.6032
  12  100          8          0.998            1.0145        -0.4169
  13  100          22          1.000            0.9313        0.1664
  14  100          8          0.900            0.8040        0.2744
  15  100          10          0.986            0.9510        0.1738
  16  100          1          0.000            0.9685        0.0000
  17  100          14          0.991            0.8700        0.3395
  18  100          7          0.997            1.0546        -0.2113
  19  100          23          1.000            1.0451        -0.0246
  20  100          24          0.266            0.6392        0.1091
  21  100          20          0.995            0.8529        0.6281
  22  100          12          0.072            0.9376        -0.0406
  23  100          19          0.999            0.9366        0.0670
  24  100          14          0.998            1.0986        -0.7853
  25  100          4          0.939            1.0483        -0.0886
  26  100          26          0.993            0.9633        0.0813
  27  100          30          0.990            0.9782        -0.0191
  28  100          30          0.995            0.9124        -0.0781
  29  100          13          0.488            2.1279        -0.2548
  30  100          18          0.283            1.2442        0.0585
  31  100          23          0.995            0.9249        0.4751
  32  100          22          0.293            2.7799        -0.1715
  33  100          7          1.000            1.0706        -0.2011
  34  100          6          0.987            0.9888        -0.0007
  35  100          8          0.989            0.9895        -0.1751
  36  100          23          0.985            0.8494        0.3038
  37  100          8          0.966            0.7378        -0.0108
  38  100          7          1.000            1.1335        -0.0927
  39  100          11          0.982            0.9994        -0.5811
  40  100          16          0.994            0.7549        0.8741
  41  100          12          0.986            0.9478        -0.4168
  42  100          11          0.994            0.8285        0.7668
  43  100          9          0.997            0.9595        -0.2219
  44  100          15          1.000            0.8666        0.2884
  45  100          13          0.517            1.6433        0.0034
  46  100          13          0.296            1.4431        -0.0938
  47  100          18          0.857            0.9734        0.3337
  48  100          13          0.999            0.9627        0.2611
  49  100          22          0.991            0.8798        0.2976
  50  100          14          0.999            1.1206        -1.0748
  51  100          10          0.999            0.9296        0.5194
  52  100          8          0.899            1.3901        0.0190
  53  100          24          0.998            1.0383        -0.3979
  54  100          7          0.998            1.1332        -0.5519
  55  100          8          0.993            0.9258        -0.0688
  56  100          19          0.992            0.9138        0.0326
  57  100          5          0.994            0.9209        -0.2679
  58  100          22          0.996            0.8591        0.6813
  59  100          7          0.650            1.5471        -0.0597
  60  100          21          0.995            0.9013        0.0722
  61  100          16          0.998            0.8689        0.4326
  62  100          1          0.002            0.7717        0.0000
  63  100          6          0.995            0.9921        0.0243
  64  100          14          0.998            0.9398        -0.5243
  65  100          12          0.515            1.7489        -0.0858
  66  100          17          0.999            0.9457        0.0390
  67  100          9          0.840            0.7706        0.5165
  68  100          6          0.969            0.9477        0.0164
  69  100          12          0.999            0.9503        -0.1039
  70  100          10          0.949            0.8026        -0.1336
  71  100          4          0.689            2.0681        0.0039
  72  100          29          0.999            1.1291        -0.6696
  73  100          5          -0.316            0.4326        0.0269
  74  100          13          -0.233            1.4081        -0.0231
  75  100          21          0.991            0.9722        -0.0179
  76  100          27          0.996            0.9971        -0.7051
  77  100          26          0.090            0.9911        0.0042
  78  100          33          0.999            1.0320        -0.1129
  79  100          19          0.990            0.9761        -0.1856
  80  100          9          -0.405            0.6967        0.0026
  81  100          37          1.000            0.9449        -0.3532
  82  100          39          0.998            0.9688        -0.3311
  83  100          16          0.996            0.9339        0.3853
  84  100          4          0.999            0.8844        0.1728
  85  100          0          0.000            1.0000        0.0000
  86  100          4          1.000            1.0431        -0.8447
  87  100          20          0.998            0.9432        0.0283
  88  100          16          0.999            0.9415        0.2914
  89  100          39          0.995            0.9713        -0.2225
  90  100          15          0.992            1.0039        0.0773
  91  100          7          0.997            1.0149        -0.4369
  92  100          15          0.713            0.9845        -0.0447
  93  100          21          0.249            0.8322        -0.0360
  94  100          34          0.997            0.9991        -0.1059
  95  100          6          0.582            0.6511        0.1327
  96  100          8          0.988            0.8068        0.5740
  97  100          16          0.989            0.9331        0.4112
  98  100          13          0.974            0.9556        0.0624
  99  100          15          0.400            0.5817        -0.0325
 
We note that there are many datasets with high correlation coefficients. We use some of those to generate the REFERENCE_DATA_SET for the second round - XSCALE.INP is now
 
OUTPUT_FILE=../reference.ahkl
INPUT_FILE=../xtal002/XDS_ASCII.HKL
INPUT_FILE=../xtal003/XDS_ASCII.HKL
INPUT_FILE=../xtal005/XDS_ASCII.HKL
INPUT_FILE=../xtal006/XDS_ASCII.HKL
INPUT_FILE=../xtal007/XDS_ASCII.HKL
INPUT_FILE=../xtal008/XDS_ASCII.HKL
INPUT_FILE=../xtal011/XDS_ASCII.HKL
INPUT_FILE=../xtal012/XDS_ASCII.HKL
INPUT_FILE=../xtal013/XDS_ASCII.HKL
INPUT_FILE=../xtal015/XDS_ASCII.HKL
INPUT_FILE=../xtal017/XDS_ASCII.HKL
INPUT_FILE=../xtal018/XDS_ASCII.HKL
INPUT_FILE=../xtal019/XDS_ASCII.HKL
INPUT_FILE=../xtal100/XDS_ASCII.HKL
 
we could have included more datasets but it's pretty clear that these 14 already provide a completeness of 34.5% :
 
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
 
    8.05        111      92      304      30.3%      3.1%      4.2%      34  17.02    4.1%    3.7%    0%  0.000      0
    5.69        198    161      515      31.3%      3.5%      3.4%      70  16.78    4.8%    3.6%    0%  0.000      0
    4.65        289    230      639      36.0%      3.2%      3.5%      109  16.77    4.4%    3.8%    0%  0.000      0
    4.03        354    267      753      35.5%      3.4%      3.6%      151  18.70    4.5%    3.1%  -40%  1.012      2
    3.60        367    287      840      34.2%      2.4%      3.6%      147  17.35    3.2%    3.1%    0%  0.000      0
    3.29        408    326      919      35.5%      3.7%      3.6%      158  16.91    5.1%    4.0%    0%  0.000      0
    3.04        422    324      987      32.8%      3.8%      3.9%      180  14.95    5.1%    4.0%    0%  0.000      0
    2.85        498    387      1066      36.3%      5.2%      4.6%      212  12.72    7.1%    7.3%    0%  0.000      0
    2.68        523    402      1124      35.8%      5.5%      5.4%      219  11.28    7.4%    7.2%    0%  0.000      0
    2.55        512    399      1174      34.0%      5.8%      6.0%      210    9.98    7.9%    7.6%    0%  0.000      0
    2.43        558    426      1263      33.7%      8.7%      8.6%      237    8.37    11.7%    12.6%  -100%  0.829      2
    2.32        589    446      1287      34.7%      8.1%      9.0%      261    8.05    11.0%    14.0%    61%  0.690      3
    2.23        621    470      1350      34.8%      9.6%    10.4%      276    7.52    12.9%    16.8%    0%  0.000      0
    2.15        653    487      1380      35.3%      8.0%      8.8%      298    7.70    10.8%    13.5%    -2%  0.783      6
    2.08        624    493      1459      33.8%      11.6%    11.6%      247    6.57    16.0%    16.0%    0%  0.000      0
    2.01        660    510      1494      34.1%      11.3%    11.5%      271    6.16    15.0%    16.7%  -100%  0.382      2
    1.95        697    535      1546      34.6%      13.1%    13.8%      295    5.34    17.7%    22.9%    0%  0.000      0
    1.90        765    576      1571      36.7%      15.9%    16.3%      351    5.12    21.7%    23.9%    0%  0.000      0
    1.85        751    563      1635      34.4%      21.7%    22.0%      339    3.80    29.3%    35.2%    0%  0.000      0
    1.80        697    531      1660      32.0%      24.5%    25.5%      298    3.51    33.1%    40.5%  -11%  0.784      2
    total      10297    7912    22966      34.5%      5.6%      5.9%    4363    9.17    7.6%    11.5%    -9%  0.741      24
 
== second round of bootstrap ==
 
Now we are ready to run our script "bootstrap.rc" a second time. Actually it would be enough to run the CORRECT step but since it only takes 2 minutes we don't bother to change the script. After this, we run xscale a third time, using the same XSCALE.INP (with all its 100 INPUT_FILE= lines) as the first time. The result is
 
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        794    270      304      88.8%      4.4%      4.2%      729  23.94    5.1%    3.0%    76%  1.884      48
    5.69        1495    478      515      92.8%      4.6%      4.5%    1404  23.48    5.4%    3.3%    73%  1.633      80
    4.65        1936    598      639      93.6%      5.4%      5.3%    1827  24.31    6.3%    3.7%    66%  1.541    133
    4.03        2381    714      752      94.9%      4.5%      4.8%    2266  24.56    5.3%    3.2%    47%  1.157    151
    3.60        2536    786      841      93.5%      5.5%      5.8%    2409  23.59    6.6%    3.9%    46%  1.164    173
    3.29        2832    875      918      95.3%      5.5%      5.7%    2693  23.10    6.5%    3.8%    31%  1.013    189
    3.04        3132    916      987      92.8%      5.7%      5.9%    3014  21.78    6.7%    3.8%    19%  0.917    228
    2.85        3383    1014      1067      95.0%      7.1%      7.1%    3234  18.61    8.3%    5.7%    26%  0.963    233
    2.68        3688    1079      1126      95.8%      8.3%      8.2%    3545  16.88    9.7%    6.9%    16%  0.911    270
    2.55        3709    1109      1171      94.7%      9.6%      9.8%    3530  14.93    11.3%    8.5%    15%  0.855    252
    2.43        4037    1194      1266      94.3%      10.8%    11.5%    3855  12.86    12.7%    11.1%    9%  0.805    287
    2.32        4160    1217      1281      95.0%      11.7%    12.4%    3979  12.14    13.6%    10.1%    13%  0.886    312
    2.23        4349    1286      1354      95.0%      12.1%    12.9%    4181  11.73    14.3%    13.5%    8%  0.738    317
    2.15        4599    1324      1378      96.1%      13.6%    14.3%    4416  11.26    15.9%    12.9%    5%  0.841    341
    2.08        4726    1379      1459      94.5%      15.5%    16.6%    4548    9.98    18.1%    14.6%    -3%  0.784    352
    2.01        4729    1419      1500      94.6%      15.6%    16.5%    4521    9.46    18.3%    16.4%    6%  0.818    338
    1.95        4980    1480      1544      95.9%      20.3%    20.3%    4782    8.20    23.9%    21.1%    -2%  0.778    353
    1.90        5217    1511      1575      95.9%      22.7%    23.7%    5016    7.51    26.5%    23.6%    -4%  0.740    391
    1.85        5232    1555      1626      95.6%      29.8%    31.0%    5015    5.91    34.9%    28.6%    5%  0.813    359
    1.80        5024    1511      1669      90.5%      33.5%    34.6%    4790    5.25    39.4%    36.9%    -1%  0.767    347
    total      72939  21715    22972      94.5%      8.2%      8.5%    69754  13.36    9.7%    10.3%    16%  0.891    5154
 
so the data are practically complete, and actually quite good. The anomalous signal suggests that it may be possible to solve the structure from its anomalous signal.
 
We can find out the correct spacegroup (19 !) with "pointless xdsin temp.ahkl", and adjust our script accordingly.
 
Now we do another round, since the completeness is so good. We can then identify those few datasets which are still not indexed in the right setting, and fix those manually. It was only xtal085 which had a problem - it turned out that the indexing had not found the correct lattice, which was fixed with STRONG_PIXEL=6.
 
The final XSCALE.LP is then:
 
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        804    276      316      87.3%      4.4%      4.2%      733  23.80    5.1%    3.1%    75%  1.899      49
    5.69        1509    481      520      92.5%      4.5%      4.4%    1416  23.61    5.2%    3.3%    75%  1.660      81
    4.65        1951    601      644      93.3%      4.3%      4.4%    1842  24.49    5.1%    3.3%    68%  1.579    134
    4.03        2402    715      755      94.7%      4.1%      4.4%    2289  24.75    4.8%    3.2%    44%  1.174    153
    3.60        2555    788      843      93.5%      4.0%      4.5%    2427  23.81    4.7%    3.2%    48%  1.169    179
    3.29        2862    877      921      95.2%      4.2%      4.7%    2724  23.35    5.0%    3.2%    31%  1.050    198
    3.04        3146    916      989      92.6%      5.0%      5.1%    3030  22.00    5.8%    4.0%    15%  0.897    231
    2.85        3399    1016      1070      95.0%      5.9%      6.1%    3251  18.75    7.0%    5.4%    28%  0.992    235
    2.68        3717    1081      1128      95.8%      7.2%      7.2%    3579  17.01    8.4%    7.1%    13%  0.883    274
    2.55        3724    1110      1174      94.5%      8.3%      8.6%    3543  15.03    9.7%    8.0%    15%  0.836    255
    2.43        4058    1196      1266      94.5%      9.9%    10.6%    3877  12.96    11.5%    10.3%    8%  0.811    291
    2.32        4190    1220      1283      95.1%      11.1%    11.8%    4013  12.21    12.9%    10.8%    11%  0.889    328
    2.23        4371    1288      1357      94.9%      11.5%    12.4%    4207  11.79    13.6%    12.6%    4%  0.757    318
    2.15        4626    1324      1378      96.1%      13.2%    13.9%    4444  11.33    15.4%    12.4%    8%  0.835    349
    2.08        4756    1383      1461      94.7%      15.2%    16.2%    4577  10.02    17.8%    14.2%    -4%  0.771    356
    2.01        4755    1423      1503      94.7%      15.4%    16.1%    4543    9.51    18.1%    15.2%    5%  0.817    342
    1.95        4995    1480      1544      95.9%      20.1%    19.9%    4794    8.24    23.6%    20.2%    -5%  0.787    359
    1.90        5242    1512      1577      95.9%      22.3%    23.2%    5034    7.55    26.1%    22.2%    -1%  0.772    400
    1.85        5261    1552      1626      95.4%      29.6%    30.6%    5054    5.95    34.6%    28.3%    6%  0.828    365
    1.80        5066    1514      1672      90.6%      33.4%    34.4%    4829    5.25    39.2%    35.7%    -1%  0.789    356
    total      73389  21753    23027      94.5%      7.4%      7.7%    70206  13.45    8.6%    9.8%    15%  0.898    5253
 
When inspecting the list of R-factors of each of the datasets it becomes clear that some of them are really good, but others are mediocre.
 
== Optimizing the result ==
 
One method to improve XDS' knowledge of geometry would be to use all 15 frames for indexing, but still only to integrate frame 1. This is easily accomplished by changing in the script:
JOB=XYCORR INIT COLSPOT IDXREF DEFPIX
DATA_RANGE=1 15
SPOT_RANGE=1 15
and to use, instead of "xds >& xds.log &" the line "../../run_xds.rc &" with the following run_xds.rc :
<pre>
#!/bin/csh -f
xds
egrep -v 'DATA_RANGE|JOB' XDS.INP >x
echo JOB=INTEGRATE CORRECT >XDS.INP
echo DATA_RANGE=1 1 >> XDS.INP
cat x >> XDS.INP
xds
</pre>
Furthermore it seems good to change "sleep 1" to "sleep 5" because now each COLSPOT has to look at 15 frames, not one. Thus, this takes a little bit longer. Indeed the result is a bit better:
 
WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        798    274      304      90.1%      4.4%      4.2%      726  23.88    5.2%    3.1%    71%  1.932      49
    5.69        1514    480      515      93.2%      4.5%      4.5%    1421  23.66    5.3%    3.4%    76%  1.670      83
    4.65        1951    599      639      93.7%      4.3%      4.4%    1845  24.57    5.0%    3.3%    67%  1.561    139
    4.03        2399    713      753      94.7%      4.1%      4.5%    2289  24.76    4.8%    3.1%    44%  1.176    154
    3.60        2546    786      840      93.6%      3.9%      4.5%    2417  23.78    4.6%    3.1%    46%  1.127    175
    3.29        2864    876      919      95.3%      4.2%      4.7%    2729  23.35    4.9%    3.2%    38%  1.018    199
    3.04        3154    918      987      93.0%      5.0%      5.2%    3037  21.98    5.8%    3.9%    18%  0.922    231
    2.85        3387    1015      1066      95.2%      5.9%      6.1%    3235  18.74    7.0%    5.2%    26%  0.992    235
    2.68        3724    1082      1126      96.1%      7.2%      7.2%    3583  17.03    8.4%    6.7%    15%  0.890    278
    2.55        3720    1111      1172      94.8%      8.3%      8.6%    3536  15.02    9.7%    8.1%    14%  0.857    255
    2.43        4079    1198      1267      94.6%      9.8%    10.6%    3898  12.96    11.5%    10.3%    9%  0.781    290
    2.32        4199    1221      1283      95.2%      11.1%    11.7%    4024  12.21    12.9%    10.8%    12%  0.911    331
    2.23        4365    1282      1350      95.0%      11.4%    12.2%    4205  11.87    13.4%    12.6%    3%  0.729    319
    2.15        4651    1332      1386      96.1%      13.3%    13.9%    4468  11.30    15.5%    12.5%    5%  0.821    354
    2.08        4745    1380      1455      94.8%      15.0%    16.0%    4569  10.04    17.6%    14.0%    -1%  0.760    358
    2.01        4744    1418      1496      94.8%      15.4%    16.0%    4531    9.50    18.1%    16.3%    5%  0.820    343
    1.95        5019    1487      1550      95.9%      19.6%    19.7%    4813    8.27    23.0%    19.7%    -1%  0.765    359
    1.90        5210    1504      1571      95.7%      21.9%    22.9%    5007    7.53    25.6%    22.8%    -6%  0.740    399
    1.85        5272    1561      1633      95.6%      29.1%    30.1%    5054    5.98    34.1%    28.8%    4%  0.801    366
    1.80        5054    1505      1659      90.7%      33.2%    34.1%    4822    5.25    38.9%    35.2%    -1%  0.790    354
    total      73395  21742    22971      94.6%      7.3%      7.7%    70209  13.46    8.6%    9.8%    16%  0.890    5271
 
but there does not appear a "magic bullet" that would produce much better data than with the quick bootstrap approach.
 
== Trying to solve the structure ==
 
First, we repeat xscale after inserting FRIEDEL'S_LAW=FALSE into XSCALE.INP . This gives us
      NOTE:      Friedel pairs are treated as different reflections.
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        804    382      476      80.3%      3.1%      3.4%      665  24.13    3.9%    2.7%    81%  2.507      50
    5.69        1527    723      882      82.0%      3.4%      3.6%    1251  22.48    4.2%    3.1%    85%  2.223      87
    4.65        1956    938      1136      82.6%      3.4%      3.6%    1602  22.73    4.3%    3.0%    72%  1.821    141
    4.03        2400    1136      1357      83.7%      3.5%      3.6%    1943  22.62    4.4%    3.2%    46%  1.347    154
    3.60        2549    1261      1533      82.3%      3.4%      3.7%    2053  21.53    4.3%    3.3%    51%  1.322    176
    3.29        2867    1393      1694      82.2%      3.7%      3.9%    2347  21.22    4.7%    3.5%    35%  1.159    199
    3.04        3154    1507      1830      82.3%      4.5%      4.3%    2607  19.33    5.7%    4.5%    17%  1.016    231
    2.85        3389    1649      1979      83.3%      5.3%      5.2%    2761  16.37    6.7%    6.0%    27%  1.054    235
    2.68        3724    1757      2104      83.5%      6.5%      6.1%    3088  14.63    8.1%    7.8%    15%  0.962    278
    2.55        3720    1813      2197      82.5%      7.3%      7.6%    2999  12.84    9.2%    9.1%    16%  0.896    255
    2.43        4079    1933      2384      81.1%      9.0%      9.5%    3352  11.01    11.3%    12.5%    9%  0.840    290
    2.32        4199    2006      2420      82.9%      10.0%    10.5%    3474  10.17    12.7%    13.8%    14%  0.939    331
    2.23        4363    2099      2551      82.3%      10.6%    11.0%    3595    9.91    13.4%    14.5%    5%  0.790    319
    2.15        4651    2203      2634      83.6%      12.2%    12.5%    3827    9.29    15.3%    15.7%    7%  0.856    354
    2.08        4745    2248      2758      81.5%      14.2%    14.7%    3945    8.32    18.0%    18.7%    -2%  0.822    358
    2.01        4744    2287      2843      80.4%      14.3%    14.6%    3896    7.92    18.1%    19.2%    7%  0.868    343
    1.95        5019    2429      2945      82.5%      18.5%    18.3%    4079    6.76    23.3%    24.6%    0%  0.789    359
    1.90        5210    2484      3000      82.8%      20.4%    21.0%    4282    6.06    25.6%    27.9%    -4%  0.757    399
    1.85        5272    2569      3119      82.4%      27.8%    28.0%    4272    4.77    35.0%    36.5%    4%  0.803    366
    1.80        5054    2451      3171      77.3%      30.9%    31.1%    4092    4.20    39.0%    43.1%    -3%  0.788    354
    total      73426  35268    43013      82.0%      6.5%      6.7%    60130  11.57    8.2%    11.7%    20%  0.963    5279
 
 
One hint towards the contents of the "crystal" is that the information about the simulated data contained the strings "1g1c". This structure (spacegroup 19, cell axes 38.3, 78.6, 79.6) is available from the PDB; it contains 2 chains of 99 residues, and a chain has 2 Cys and 2 Met. Thus we assume that the simulated data may represent SeMet-SAD. Using [[ccp4:hkl2map|hkl2map]], we can easily find four sites with good CCall/CCweak:
 
[[File:Simulated-1g1c-ccall-ccweak2.png]]
[[File:Simulated-1g1c-hist2.png]]
[[File:Simulated-1g1c-occ2.png]]
[[File:Simulated-1g1c-contrast-vs-cycle2.png]]
 
I also tried the poly-Ala tracing feature of shelxe:
 
shelxe.beta -m40 -a -q -h -s0.54 -b -i -e -n 1g1c 1g1c_fa
 
but it traces only about 62 residues. The density looks somewhat reasonable, though.
 
The files [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-I.mtz xds-simulated-1g1c-I.mtz] and [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-F.mtz xds-simulated-1g1c-F.mtz] are available.
 
I refined against 1g1c.pdb:
phenix.refine xds-simulated-1g1c-F.mtz 1g1c.pdb refinement.input.xray_data.r_free_flags.generate=True
The result was
Start R-work = 0.3453, R-free = 0.3501
Final R-work = 0.2170, R-free = 0.2596
which appears reasonable.
 
== Notes ==
 
=== Towards better completeness: using the first two frames instead of only the first ===
 
We might want better (anomalous) completeness than what is given by only the very first frame of each dataset. To this end, we change in the XDS.INP part of our script :
DATA_RANGE=1 2
then run the script which reduces the 100 datasets. When this has finished, we insert in XSCALE.INP
NBATCH=2
after each INPUT_FILE line (this can be easily done using <pre> awk '{print $0;print "NBATCH=2"}' XSCALE.INP > x </pre>). The reason for this is that by default, XSCALE establishes scalefactors every 5 degrees, but here we want scalefactors for every frame, because the radiation damage is so strong. This gives:
      NOTE:      Friedel pairs are treated as different reflections.
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        1922    467      476      98.1%      4.2%      6.6%    1888  20.04    4.8%    2.8%    84%  1.887    142
    5.69        3494    864      882      98.0%      4.5%      6.8%    3429  18.67    5.2%    3.1%    83%  1.635    297
    4.65        4480    1111      1136      97.8%      5.3%      6.7%    4395  18.89    6.1%    3.5%    66%  1.347    406
    4.03        5197    1325      1357      97.6%      6.2%      6.8%    5101  18.37    7.1%    4.3%    43%  1.156    499
    3.60        5916    1500      1533      97.8%      6.9%      7.1%    5804  17.83    8.0%    4.7%    36%  1.083    572
    3.29        6601    1657      1694      97.8%      7.6%      7.3%    6476  17.26    8.7%    4.9%    24%  1.029    634
    3.04        7081    1789      1830      97.8%      9.1%      8.0%    6949  15.50    10.4%    6.4%    17%  1.011    693
    2.85        7684    1946      1979      98.3%      10.9%      9.9%    7530  12.95    12.5%    8.1%    16%  0.950    751
    2.68        8101    2062      2100      98.2%      13.1%    12.1%    7935  11.18    15.0%    10.5%    10%  0.888    795
    2.55        8355    2156      2201      98.0%      15.2%    14.9%    8182    9.69    17.5%    12.3%    6%  0.867    837
    2.43        9195    2327      2376      97.9%      18.2%    18.6%    9003    8.20    20.8%    15.4%    6%  0.837    904
    2.32        9495    2377      2428      97.9%      21.3%    21.9%    9304    7.42    24.4%    18.4%    6%  0.800    934
    2.23        9939    2499      2551      98.0%      23.0%    23.3%    9753    7.13    26.4%    19.0%    4%  0.818    987
    2.15      10219    2577      2622      98.3%      25.4%    25.9%    9992    6.63    29.1%    20.6%    1%  0.797    998
    2.08      10712    2704      2766      97.8%      29.4%    30.8%    10508    5.80    33.8%    25.1%    4%  0.793    1071
    2.01      10900    2778      2839      97.9%      30.8%    31.2%    10649    5.50    35.3%    26.2%    4%  0.828    1060
    1.95      11361    2878      2937      98.0%      36.7%    38.2%    11134    4.71    42.1%    31.5%    1%  0.768    1136
    1.90      11641    2943      3000      98.1%      42.7%    45.1%    11405    4.12    49.1%    38.7%    -1%  0.775    1165
    1.85      12028    3069      3123      98.3%      54.0%    60.4%    11760    3.19    62.1%    47.5%    5%  0.735    1196
    1.80      11506    3003      3173      94.6%      62.1%    70.6%    11229    2.72    71.6%    60.6%    -2%  0.709    1148
    total      165827  42032    43003      97.7%      12.8%    13.3%  162426    8.79    14.7%    15.7%    15%  0.881  16225
 
showing that the anomalous completeness, and even the quality of the anomalous signal, can indeed be increased. I doubt, however, that going to three or more frames would improve things even more.
 
The MTZ files are at [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-F-2frames.mtz] and [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-I-2frames.mtz], respectively. They were of course obtained with XDSCONV.INP:
INPUT_FILE=temp.ahkl
OUTPUT_FILE=temp.hkl CCP4_I
for the intensities, and
INPUT_FILE=temp.ahkl
OUTPUT_FILE=temp.hkl CCP4
for the amplitudes. In both cases, after xdsconv we have to run
<pre>
f2mtz HKLOUT temp.mtz<F2MTZ.INP
cad HKLIN1 temp.mtz HKLOUT output_file_name.mtz<<EOF
LABIN FILE 1 ALL
END
EOF
</pre>
 
Using the default (see above) phenix.refine job, I obtain against the [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-F-2frames.mtz MTZ file with amplitudes]:
Start R-work = 0.3434, R-free = 0.3540
Final R-work = 0.2209, R-free = 0.2479
and against the [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xds-simulated-1g1c-I-2frames.mtz MTZ file with intensities]
Start R-work = 0.3492, R-free = 0.3606
Final R-work = 0.2244, R-free = 0.2504
 
so: '''better R-free is obtained from better data.'''
 
The statistics from SHELXD and SHELXE don't look better - they were already quite good with a single frame per dataset. The statistics printed by SHELXE (for the correct hand) are:
...
<wt> = 0.300, Contrast = 0.591, Connect. = 0.740 for dens.mod. cycle 50
Estimated mean FOM and mapCC as a function of resolution
d    inf - 3.98 - 3.13 - 2.72 - 2.47 - 2.29 - 2.15 - 2.04 - 1.95 - 1.87 - 1.81
<FOM>  0.601  0.606  0.590  0.570  0.538  0.542  0.521  0.509  0.529  0.498
<mapCC> 0.841  0.813  0.811  0.786  0.763  0.744  0.727  0.740  0.761  0.722
N        2289  2303  2334  2245  2289  2330  2299  2297  2429  2046
Estimated mean FOM = 0.551  Pseudo-free CC = 59.42 %
...
Site    x      y      z  h(sig) near old  near new
  1  0.7375  0.6996  0.1537  20.4  1/0.06  2/15.05 6/21.38 3/21.54 5/22.03
  2  0.7676  0.7231  0.3419  18.8  3/0.13  5/12.15 1/15.05 3/21.34 4/22.43
  3  0.5967  0.4904 -0.0067  17.2  4/0.10  4/4.90 6/4.94 2/21.34 1/21.54
  4  0.5269  0.5194 -0.0498  17.1  2/0.05  3/4.90 6/7.85 2/22.43 1/22.96
  5  0.4857  0.6896  0.4039  -4.8  3/12.04  2/12.15 1/22.03 3/22.55 2/22.85
  6  0.5158  0.4788  0.0406  4.7  5/1.45  3/4.94 4/7.85 1/21.38 5/23.30
 
=== Why this is difficult to solve with SAD phasing ===
 
In the original publication ("Structural evidence for a possible role of reversible disulphide bridge formation in the elasticity of the muscle protein titin" Mayans, O., Wuerges, J., Canela, S., Gautel, M., Wilmanns, M. (2001) Structure 9: 331-340 ) we read:
 
"This crystal form contains two molecules in the asymmetric unit. They are related by a noncrystallographic two-fold axis, parallel to the crystallographic b axis, located at X = 0.25 and Z = 0.23. This arrangement results in a peak in the native Patterson map at U = 0.5, V = 0, W = 0.47 of peak height 26 σ (42% of the origin peak)."
 
Unfortunately, the arrangement of substructure sites has (pseudo-)translational symmetry, and may be related to a centrosymmetric arrangement. Indeed, the original structure was solved using molecular replacement.
 
Using the four sites as given by SHELXE (and default parameters otherwise), I obtained from the [http://cci.lbl.gov/cctbx/phase_o_phrenia.html cctbx - Phase-O-Phrenia server] the following
Plot of relative peak heights:
    |*
    |*
    |*
    |*
    |**
    |**
    |***
    |****
    |******
    |************
    |********************
    |*****************************
    |*********************************
    |***************************************
    |************************************************
    |************************************************************
    |************************************************************
    |************************************************************
    |************************************************************
    |************************************************************
    -------------------------------------------------------------
Peak list:
  Relative
  height  Fractional coordinates
    97.8  0.01982  0.49860 -0.00250
    80.2  0.17362  0.71758  0.83714
    71.5  0.02405  0.53538  0.48365
    63.9  -0.00511  0.07044  0.50289
    62.1  0.02410  0.94827  0.48807
    61.3  0.16922  0.28605  0.15985
    56.3  0.12047  0.50910  0.43665
    55.9  0.21871  0.26331  0.30008
    55.7  0.10931  0.47245  0.53659
    53.0  0.22211  0.23746  0.39503
    52.9  0.03449 -0.00661  0.98264  <------ this peak is close to the origin
    52.5  0.06905  0.02372  0.05632  <------ this one, too
    ...
 
so the strongest peak corresponds to the translation of molecules (0,0.5,0) but the origin peak is at 1/2 of that size, which appears significant.
 
 
=== Finally solving the structure ===
 
After thinking about the most likely way that James Holton used to produce the simulated data, I hypothesized that within each frame, the radiation damage is most likely constant, and that there is a jump in radiation damage from frame 1 to 2. Unfortunately for this scenario, the scaling algorithm in CORRECT and XSCALE was changed for the version of Dec-2010, such that it produces best results when the changes are smooth. Therefore, I tried the penultimate version (May-2010) of XSCALE - and indeed that gives significantly better results:
 
      NOTE:      Friedel pairs are treated as different reflections.
SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
RESOLUTION    NUMBER OF REFLECTIONS    COMPLETENESS R-FACTOR  R-FACTOR COMPARED I/SIGMA  R-meas  Rmrgd-F  Anomal  SigAno  Nano
  LIMIT    OBSERVED  UNIQUE  POSSIBLE    OF DATA  observed  expected                                      Corr
    8.05        1922    467      476      98.1%      4.0%      5.8%    1888  22.37    4.5%    2.5%    84%  1.952    142
    5.69        3494    864      882      98.0%      4.7%      6.0%    3429  20.85    5.4%    3.2%    77%  1.707    297
    4.65        4480    1111      1136      97.8%      5.1%      5.9%    4395  21.13    5.8%    3.3%    68%  1.518    406
    4.03        5197    1325      1357      97.6%      5.3%      6.0%    5101  20.57    6.1%    3.8%    48%  1.280    499
    3.60        5915    1500      1533      97.8%      6.0%      6.3%    5803  19.99    6.9%    4.1%    41%  1.169    572
    3.29        6601    1657      1694      97.8%      6.5%      6.5%    6476  19.42    7.5%    4.6%    27%  1.066    634
    3.04        7080    1789      1830      97.8%      7.6%      7.2%    6948  17.50    8.7%    5.4%    23%  1.037    693
    2.85        7682    1945      1979      98.3%      8.8%      9.0%    7528  14.75    10.1%    7.0%    15%  0.935    750
    2.68        8099    2062      2100      98.2%      11.0%    11.1%    7933  12.81    12.7%    9.1%    13%  0.881    795
    2.55        8351    2155      2201      97.9%      13.3%    13.7%    8178  11.16    15.4%    11.0%    12%  0.872    836
    2.43        9195    2327      2376      97.9%      16.5%    17.2%    9003    9.49    19.0%    15.1%    8%  0.838    904
    2.32        9495    2377      2428      97.9%      19.8%    20.3%    9304    8.62    22.7%    17.3%    4%  0.818    934
    2.23        9936    2498      2551      97.9%      20.8%    21.7%    9751    8.30    23.9%    17.5%    4%  0.830    987
    2.15      10217    2577      2622      98.3%      23.3%    24.0%    9990    7.74    26.7%    19.2%    4%  0.814    998
    2.08      10710    2704      2766      97.8%      27.1%    28.6%    10506    6.82    31.1%    23.5%    5%  0.812    1071
    2.01      10899    2777      2839      97.8%      28.1%    29.2%    10648    6.46    32.3%    25.0%    6%  0.813    1059
    1.95      11361    2878      2937      98.0%      34.4%    35.5%    11134    5.55    39.5%    30.3%    3%  0.780    1136
    1.90      11639    2941      3000      98.0%      40.5%    41.5%    11403    4.88    46.6%    35.9%    0%  0.787    1163
    1.85      12020    3068      3123      98.2%      52.2%    55.1%    11752    3.79    60.0%    47.4%    6%  0.775    1195
    1.80      11506    3003      3173      94.6%      60.8%    64.8%    11229    3.23    70.1%    58.8%    0%  0.765    1148
    total      165799  42025    43003      97.7%      11.7%    12.3%  162399  10.07    13.5%    14.8%    17%  0.908  16219
 
Using these data (stored in [https://{{SERVERNAME}}/pub/xds-datared/1g1c/xscale.oldversion]), I was finally able to solve the structure (see screenshot below) - SHELXE traced 160 out of 198 residues. All files produced by SHELXE are in [https://{{SERVERNAME}}/pub/xds-datared/1g1c/shelx].
 
[[File:1g1c-shelxe.png]]
 
It is worth mentioning that James Holton confirmed that my hypothesis is true; he also says that this approach is a good approximation for a multi-pass data collection.
 
However, generally (i.e. for real data) the smooth scaling (which also applies to absorption correction and detector modulation) gives better results than the previous method of assigning the same scale factor to all reflections of a frame; in particular, it correctly treats those reflections near the border of two frames. 
 
Phenix.refine against these data gives:
Start R-work = 0.3449, R-free = 0.3560
Final R-work = 0.2194, R-free = 0.2469
which is only 0.15%/0.10% better in R-work/R-free than the previous best result (see above).
 
This example shows that it is important to
* have the best data available if a structure is difficult to solve
* know the options (programs, algorithms)
* know as much as possible about the experiment
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