Scale many datasets: Difference between revisions

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=== Step 2: process a single dataset to get an idea of spacegroup, cell and resolution. ===

This was done for the (randomly chosen) X1 dataset. Turns out that it is cubic insulin, spacegroup I213 with cell about 78 78 78 90 90 90. The XDS_ASCII.HKL of that was saved as x1_as_reference.hkl to serve as REFERENCE_DATA_SET for all other datasets, to ensure consistent indexing, because otherwise the possibility of re-indexing would have to be considered. This can be done by xscale_isocluster but it is easier to use a REFERENCE_DATA_SET if one exists.

This was done for the (randomly chosen) X1 dataset. Turns out that it is cubic insulin, spacegroup I213 with cell about 78 78 78 90 90 90. The XDS_ASCII.HKL of that was saved as x1_as_reference.hkl to serve as REFERENCE_DATA_SET for all other datasets, to ensure consistent indexing, because otherwise the possibility of re-indexing would have to be considered. This can be done by [[xscale_isocluster]] but it is easier to use a REFERENCE_DATA_SET if one exists.

=== Step 3: create 36 directories, named according to the unique parts of the filenames. ===

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</pre>

=== Step 6: analyze resulting XSCALE.HKL to find 3 groups of datasets ===

=== Step 6: analyze, using [[xscale_isocluster]], the resulting XSCALE.HKL to find 3 groups of datasets ===

... representing pig, cow and human insulin, respectively (but of course it is not clear which group is which organism; one could look at the 1.2A electron density maps and compare with sequences).

<pre>

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</pre>

This pseudo-PDB file can be visualized in coot or so and shows three groups, consisting of datasets 1-12, 13-24 and 25-36, around coordinates (99,0,10), (98,10,-8) and (99,-13,-5), respectively. This sequential ordering agrees with the fact that the datasets were processed according to their names. In other words, the three groups found by [[xscale_isocluster]] correspond to the three different organisms, as expected.

An even better way is to run

xscale_isocluster -clu 3 XSCALE.HKL

and this will give you three output files XSCALE.1.INP XSCALE.2.INP XSCALE.3.INP each with the correct 12 datasets.

Thanks, Graeme! This is nice and shows the possibility to differentiate between crystals of different but similar content.

@@ Line 14: / Line 14: @@
 === Step 2: process a single dataset to get an idea of spacegroup, cell and resolution. ===
-This was done for the (randomly chosen) X1 dataset. Turns out that it is cubic insulin, spacegroup I213 with cell about 78 78 78 90 90 90. The XDS_ASCII.HKL of that was saved as x1_as_reference.hkl to serve as REFERENCE_DATA_SET for all other datasets, to ensure consistent indexing, because otherwise the possibility of re-indexing would have to be considered. This can be done by xscale_isocluster but it is easier to use a REFERENCE_DATA_SET if one exists.
+This was done for the (randomly chosen) X1 dataset. Turns out that it is cubic insulin, spacegroup I213 with cell about 78 78 78 90 90 90. The XDS_ASCII.HKL of that was saved as x1_as_reference.hkl to serve as REFERENCE_DATA_SET for all other datasets, to ensure consistent indexing, because otherwise the possibility of re-indexing would have to be considered. This can be done by [[xscale_isocluster]] but it is easier to use a REFERENCE_DATA_SET if one exists.
 === Step 3: create 36 directories, named according to the unique parts of the filenames. ===
@@ Line 77: / Line 77: @@
 </pre>
-=== Step 6: analyze resulting XSCALE.HKL to find 3 groups of datasets ===
+=== Step 6: analyze, using [[xscale_isocluster]], the resulting XSCALE.HKL to find 3 groups of datasets ===
 ... representing pig, cow and human insulin, respectively (but of course it is not clear which group is which organism; one could look at the 1.2A electron density maps and compare with sequences).
 <pre>
@@ Line 123: / Line 123: @@
 </pre>
 This pseudo-PDB file can be visualized in coot or so and shows three groups, consisting of datasets 1-12, 13-24 and 25-36, around coordinates (99,0,10), (98,10,-8) and (99,-13,-5), respectively. This sequential ordering agrees with the fact that the datasets were processed according to their names. In other words, the three groups found by [[xscale_isocluster]] correspond to the three different organisms, as expected.
+An even better way is to run
+ xscale_isocluster -clu 3 XSCALE.HKL
+and this will give you three output files XSCALE.1.INP XSCALE.2.INP XSCALE.3.INP each with the correct 12 datasets.
 Thanks, Graeme! This is nice and shows the possibility to differentiate between crystals of different but similar content.