Use the GUI
Just feed the 2 sca files into pointless - choose one as the reference -
it really shouldnt match which..
pointless will check the indexing is consistent, then give you an output
file with the two sets merged and sorted together, with different batch
numbers assigned.
scala will then scale them.
You will need use your judgement to decide on resolution limits for the
two runs. Presumably your high resolution data set has saturated spots
in the low resolution shell, and if they dont merge properly it may be
best to exclude the low resolution.
Eleanor
On 05/30/2011 07:50 PM, Tim Gruene wrote:
Dear pengfei,
you do not need to use mosflm if you want to scale the datasets with scala. You
can use scalepack2mtz (available from ccp4i -> Program List) to convert the two
sca-files to mtz-format and then use scala for scaling.
Maybe HKL2000/scalepack can scale the files for you if you integrate them both
in the same run (load both data sets, and HKL2000 will integrate both data
sets).
Tim
On Tue, May 31, 2011 at 02:40:49AM +0800, Pengfei Fang wrote:
Hi David,
Thanks for your help. I just scaled the two data sets independently using
HKL2000.
And, I don't know how to set reference in HKL2000 or CCP4.
If using CCP4, should I also use imosflm to do integrate?
thanks,
pengfei
At 2011-05-31 02:32:03，"David Veesler"<david.vees...@afmb.univ-mrs.fr> wrote:
Hi Pengfei,
you can combine your files using pointless but it is unclear to me based on
your message if you have scaled independently the two data sets or not.
You should scale these two data sets together using one as reference (doable
using XSCALE or SCALA...).
Cheers
David
Le 30 mai 2011 à 11:13, Pengfei Fang a écrit :
Dear All,
I have two data sets from one crystal.
One had short exposures to keep the low resolution reflections from saturating.
The other had long exposure to get high resolution data.
I am wondering how two merge these two data sets into one file that I can use
for refinement.
The two sets already scaled by HKL2000. Now I have two .sca files.
Thanks a lot!
Pengfei Fang
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