XDSCC12 is a program for generating delta-CC1/2 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 , 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.
Usage (this text can be obtained with
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. The isomorphous delta-CC1/2 of a batch of frames (width chosen with the -t option) relative to all data is most easily visualized via XDSGUI (Statistics tab); the anomalous delta-CC1/2 may be plotted with e.g. gnuplot after grepping the relevant lines from the output.
For multiple datasets, the output lines show the contribution of each dataset toward the total CC1/2. 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.