Hi, a random thought: the data resolution, d_min_actual, can be thought of as such that maximizes the correlation (*) between the synthesis calculated using your data and an equivalent Fmodel synthesis calculated using complete set of Miller indices in d_min_actual-inf resolution range, where d_min<=d_min_actual and d_min is the highest resolution of data set in question. Makes sense to me..
(*) or any other more appropriate similarity measure: usual map CC may not be the best one in this context. Pavel On Tue, Aug 27, 2013 at 5:45 AM, Arka Chakraborty < arko.chakrabort...@gmail.com> wrote: > Hi all, > does this not again bring up the still prevailing adherence to R factors > and not a shift to correlation coefficients ( CC1/2 and CC*) ? (as Dr. > Phil Evans has indicated).? > The way we look at data quality ( by "we" I mean the end users ) needs to > be altered, I guess. > > best, > > Arka Chakraborty > > On Tue, Aug 27, 2013 at 9:50 AM, Phil Evans <p...@mrc-lmb.cam.ac.uk> wrote: > >> The question you should ask yourself is "why would omitting data improve >> my model?" >> >> Phil >> >> On 27 Aug 2013, at 02:49, Emily Golden <10417...@student.uwa.edu.au> >> wrote: >> >> > Hi All, >> > >> > I have collected diffraction images to 1 Angstrom resolution to the >> edge of the detector and 0.9A to the corner. I collected two sets, one >> for low resolution reflections and one for high resolution reflections. >> > I get 100% completeness above 1A and 41% completeness in the 0.9A-0.95A >> shell. >> > >> > However, my Rmerge in the highest shelll is not good, ~80%. >> > >> > The Rfree is 0.17 and Rwork is 0.16 but the maps look very good. If I >> cut the data to 1 Angstrom the R factors improve but I feel the maps are >> not as good and I'm not sure if I can justify cutting data. >> > >> > So my question is, should I cut the data to 1Angstrom or should I keep >> the data I have? >> > >> > Also, taking geometric restraints off during refinement the Rfactors >> improve marginally, am I justified in doing this at this resolution? >> > >> > Thank you, >> > >> > Emily >> > > > > -- > *Arka Chakraborty* > *ibmb (Institut de Biologia Molecular de Barcelona)** > **BARCELONA, SPAIN** > * >
