Transcript Developments in xia2

Developments in
xia2
Graeme Winter
CCP4 Dev Meeting 2008
What is xia2?
Automated robust data reduction and
analysis
 Thorough – takes additional steps when
many users wouldn’t bother
 In: images from e.g. synchrotron beamline
 Out: measurements for downstream
phasing via e.g. HAPPy, Mr BUMP,
Phenix…

Recent changes
Inclusion in CCP4 6.1
 Many command line options
 Integrated with AutoRickshaw (EMBL H)
 Robust lattice determination
 Support for Q270, Pilatus
 Zero input option

3 Month plans
BioXHit ends in June => so does xia2
development
 Include robust system to decide resolution
limits etc (next slides)
 Finish release 0.3.0 to go with release
version of CCP4 6.1

Chef
Let’s cook them books!
What is chef?
A tool to help you use the best of the
reflections you have
 Uses unmerged intensities
 Uses robust statistics to decide:

 d*min
for different functions (resolution)
 Dmax for different functions (dose)

Additional program “doser” to add dose
information to unmerged MTZ files
In
MTZ files from scala with “output
unmerged” set
 DOSE / TIME information for doser:

 BATCH
1 DOSE 2.5 TIME 2.5
 BATCH 2 DOSE 7.5 TIME 8.2
…
Running
doser hklin TS03_12287_chef_INFL.mtz hklout infl.mtz < doser.in
doser hklin TS03_12287_chef_LREM.mtz hklout lrem.mtz < doser.in
doser hklin TS03_12287_chef_PEAK.mtz hklout peak.mtz < doser.in
chef hklin1 infl.mtz hklin2 lrem.mtz hklin3 peak.mtz << eof
isigma 2.0
resolution 1.65
range width 30 max 1500
print comp rd rdcu
anomalous on
labin BASE=DOSE
eof
Output
Resolution vs. dose
 Completeness vs.
dose for each data set

Methods

Based on “new” cumulative-pairwise R
factor RCP:

Inspired by Rd in Diederichs (2006)
And RCP means..?
How well do the measurements up to dose
D agree?
 Closely related to I/σ
 Reasonably robust as it does not depend
on sigma estimates or means
 Gets bigger when systematic variation
contributes to spread

Requirements

Radiation damaged MAD data – what do I
want for:
determination – big anomalous /
dispersive signal
 Phase calculation – well measured ΔF
 Phase extension & improvement – good F
 Refinement – good F
 Substructure

85% Limit RCP < R(I/σ) + S(I/σ, Nm, Nu)
Example
JCSG TB0541 – heavily radiation
damaged…
 3 wavelength MAD – INFL + LREM, PEAK
 Massive signal
 P43212, 90 degrees * 3 => plenty of data
 Chef says “use data to 1.65A, D=~600s”

Before (INFL)
For TS03/12287/INFL
High resolution limit
Low resolution limit
Completeness
Multiplicity
I/sigma
Rmerge
Rmeas(I)
Rmeas(I+/-)
Rpim(I)
Rpim(I+/-)
Wilson B factor
Anomalous completeness
Anomalous multiplicity
Anomalous correlation
1.66
52.7
95.8
6.4
13.1
0.085
0.117
0.099
0.045
0.051
19.372
95.5
3.4
0.546
7.41
52.7
98.4
5.1
25.6
0.045
0.077
0.054
0.032
0.029
1.66
1.7
72.5
4.2
2.2
0.654
0.808
0.816
0.374
0.478
100.0
3.5
0.695
72.3
2.1
0.032
After (INFL – first 60 degrees)
For TEST001/12287/LREM
High resolution limit
Low resolution limit
Completeness
Multiplicity
I/sigma
Rmerge
Rmeas(I)
Rmeas(I+/-)
Rpim(I)
Rpim(I+/-)
Wilson B factor
Anomalous completeness
Anomalous multiplicity
Anomalous correlation
1.63
52.56
92.6
4.1
13.6
0.052
0.065
0.066
0.031
0.041
18.731
91.8
2.2
-0.227
7.3
52.56
98.3
3.3
26.2
0.033
0.041
0.043
0.021
0.027
1.63
1.68
62.9
2.4
2.1
0.317
0.504
0.445
0.306
0.311
99.4
2.2
0.071
59.4
1.3
0.01
Why improvement?
Limit radiation damage => σF more
meaningful
 Limit damage => ΔF better
 Without systematic damage get higher
resolution for given I/σ

However…
Pipe MTZ through scaleit / solve / cad /
resolve / Arp/Warp and get very similar
results – slight improvement though
 This is most interesting, because it means
that 55% of the “data” did not add to the
quality of the result

Plans
Currently writing this up for J. Appl. Cryst
 Chef will be included in CCP4 6.1
 Next: include this as part of xia2 (makes
0.3.0)
 Extend chef to make decisions about
anomalous / dispersive differences
