Xdscc12

XDSCC12 is a program for generating delta-CC_1/2 values for XDS_ASCII.HKL (written by XDS), or for XSCALE.HKL containing several files of type XDS_ASCII.HKL after scaling in XSCALE (with MERGE=FALSE).

It implements the method described in Assmann, Brehm and Diederichs (2016) Identification of rogue datasets in serial crystallography. J. Appl. Cryst. 49, 1021 [1], and it does this not only for the individual datasets in XSCALE.HKL, but also for individual frames, or groups of frames, of a single dataset collected with the rotation method and processed by XDS.

The program can be downloaded for Linux 64bit or Mac.

Usage (this text can be obtained with xdscc12 -h):

usage: xdscc12 -dmin <lowres> -dmax <highres> -nbin <nbin> -mode <1 or 2> -<abcdeftwrz> FILE_NAME
dmax (default 999A), dmin (default 1A) and nbin (default 10) have the usual meanings.
mode can be 1 (equal volumes of resolution shells) or 2 (increasing volumes; default).
   -t: total oscillation (degree) to batch fine-sliced frames into
   -r: also show CC against reference dataset (e.g. Icalc from model)
other options can be combined (e.g. -def), and switch the following off:
   -a: individual isomorphous summary values
   -b: individual (Fisher-transformed) delta-CC1/2 values
   -c: individual delta-CC1/2 reflection numbers
   -d: individual anomalous summary values
   -e: individual (Fisher-transformed) delta-CC1/2ano values
   -f: individual delta-CC1/2ano reflection numbers
   -w: weighting of intensities with their sigmas
   -z: Fisher transformation of delta-CC1/2 values

The program output is terse but supposed to be self-explanatory. Part of it is most easily visualized via XDSGUI, however, that currently only deals with the isomorphous signal of a batch of frames (width chosen with the -t option) relative to all data.

For multiple datasets, the output lines show the contribution of each dataset toward the total CC_1/2. Negative numbers indicate a worsening of the overall signal.

Statistics are given (in resolution shells) for the isomorphous and the anomalous signal.

Important: to identify outliers in XSCALEd data, you should use the -w option. Otherwise, a and b are adjusted such that the sigmas are very high, which reduces the signal in delta-CC1/2.