Interesting.. I use this formula to calculate R-factor between two data sets when I cannot choose which one to call "Fobs" and which one to call "Fcalc". But clearly, this is not exact what we call R-factor.

Pavel

On 10/13/14 2:02 PM, Nathaniel Echols wrote:

On Mon, Oct 13, 2014 at 11:54 AM, Nathaniel Echols <[email protected]> wrote:

In the default phenix.refine output MTZ, the "F-obs" column will not be scaled to F-model. My guess is that your input data have already been placed on an absolute scale based on the Wilson statistics, so the results are reasonably close, but when I tried using the same commands on an XFEL dataset I got an R-factor of 192.

Okay, this statement is at least partially incorrect - your data are clearly on the correct scale in the phenix.refine output file, but the data in the file I used are not. (I'm going to blame this on the weirdness of certain XFEL data.)

However, I did eventually figure out the problem: SFTOOLS is using a different formula for the R-factor. If you give it the command "correl help", it will include this:

RFACT Rfactor in percent

( 200*Sum|col1-col2|/sum(col1+col2) )

Which disagrees with our source code, and the Rupp textbook, and Kay's wiki, and Wikipedia, all of which use sum(col1) as the denominator (assuming col1 == F-obs, but in our code it's written more generally). In other words: the R-factors from SFTOOLS cannot be meaningfully compared to the R-factors from refinement.

-Nat
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