XSCALE ISOCLUSTER: Difference between revisions

XSCALE ISOCLUSTER (view source)

Revision as of 22:22, 30 August 2019

125 bytes added , 30 August 2019

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 After segmentation of data sets in n-dimensional space, the program may be used (by specifying the -clu <m> option; default m=1) to try and identify <m> clusters of data sets. The program writes files called XSCALE.1.INP with lines required for scaling the datasets of cluster 1, and similarly XSCALE.2.INP for cluster 2, and so on. Typically, one may want to create directories cluster1 cluster2 ..., and then establish symlinks (called XSCALE.INP) in these to the XSCALE.#.INP files. This enables separate scaling of each cluster.
-Furthermore, a file iso.pdb is produced that may be loaded into coot. Then use Show/Cell and Symmetry/Show unit cell (to see the origin, which coot marks with "0"), and visualize the relations between data sets. Systematic differences are related to the angle (with the tip of the angle at the origin) between data sets; random differences are related to the lengths of the vectors (starting at the origin; short vectors correspond to noisy data sets). With the -i option, individual iso.x.pdb files can be written for each cluster. For an example, see [[SSX]].
+Furthermore, a file iso.pdb is produced that may be loaded into coot. Then use Show/Cell and Symmetry/Show unit cell (to see the origin, which coot marks with "0"), and visualize the relations between data sets. Systematic differences are related to the angle (with the tip of the angle at the origin) between the vectors that represent the data sets; ideally, in the case of isomorphous data sets all vectors point into the same direction. Random differences are related to the lengths of the vectors (starting at the origin; short vectors correspond to weak/noisy data sets). With the -i option, individual iso.x.pdb files can be written for each cluster. For an example, see [[SSX]].
 == Output ==