Dear colleagues,

I want to thank the following people for providing suggestions and comments about ‘difficult’ datasets suitable for teaching data processing:

Tim Craig

Jacob Keller

Graeme Winter

Aleksandar Bijelic

Clemens Vonrhein

Loes Kroon-Batenburg

James Holton 

If anyone else has suggestions for good datasets for teaching processing, I would still be happy to hear them.

Finally, several people asked me to make available a list of all the dataset suggestions I receive.  I am happy to do so, and I will post a message to this list when the information is up and available, probably later in the fall.

Sincerely,

Matthew  

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Matthew J. Whitley, Ph.D.
Research Instructor
Department of Pharmacology & Chemical Biology
University of Pittsburgh School of Medicine

On 9/19/2018 5:15 PM, Whitley, Matthew J wrote:

Dear colleagues,

For teaching purposes, I am looking for a small number (< 5) of
macromolecular diffraction datasets (raw images) that might be
considered 'difficult' for a beginning crystallography student to
process.  By 'difficult' I generally mean not able to be processed
automatically by a common processing package (XDS, Mosflm, DIALS, etc)
using default settings, i.e., no black box "click and done" processing.
The datasets I am looking for would have some stumbling block such as
incorrect experimental parameters recorded in the image headers,
multiple lattices that cause indexing to fail, datasets for which
determining the correct space group is tricky, datasets for experiments
in which the crystal slipped or moved in the beam, or anything else you
can think of.  The idea is for these beginning students to examine
several datasets that highlight various phenomena that can lead one
astray during processing.

A good candidate dataset would also ideally comprise a modest number of
images so as to keep integration time to a minimum.  Factors that are
mostly irrelevant for my purpose: resolution (as long as better than
~3.5 Å), source (home vs synchrotron), presence/absence of anomalous
scattering,  presence/absence of ligands, monomeric vs oligomeric
structures, etc.  Also, to be clear, I am not looking for datasets that
have so many pathologies that they would require many long hours of work
for an expert to process correctly.

I have checked public repositories such as proteindiffraction.org and
SBGrid databank, but all of the datasets I acquired from these sources
process satisfactorily with little effort, and in any event I know of no
way to search for 'challenging' datasets.  (I also wonder whether
anybody is in the habit of depositing, shall we say, less-than-pristine
images to public repositories?)

If you know of such a dataset that is already publicly available, or if
you have such a dataset that you are willing to share for solely
educational purposes, I would appreciate hearing from you, either on- or
off-list.

Thank you in advance for your suggestions.

Matthew

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