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*To*: ccp4bb@dl.ac.uk*Subject*: [ccp4bb]: Statistical advice*From*: "Eleanor J. Dodson" <ccp4@ysbl.york.ac.uk>*Date*: Mon, 12 Mar 2001 11:15:42 +0000*Organization*: Structural Biology Lab. , Dep. Of Chemistry, University of York*Reply-To*: E.Dodson@ysbl.york.ac.uk*Sender*: owner-ccp4bb@dl.ac.uk

*** For details on how to be removed from this list visit the *** *** CCP4 home page http://www.dl.ac.uk/CCP/CCP4/main.html *** Here is a statical problem at the heart of normalising isomorphous or more seriously anomalous differences. such differences ideally represent FH cos(Phi_random) or 2F"H sin s(Phi_random) where Phi_random = PHI_protein-PHI_H Normalising them is rather iffy, but since <cos (Phi_random)> or <sin(Phi_random)> = 0.5 it is possible, and anyway it seems to work! But we know that while the observed difference for any reflection should approximate to the true difference with a associated sigma, the <absolute_value> will be an overestimate, at least for the weak differences. You can see this intuitively for those reflections which should have difference = 0; since each observation has an associated Sigma, the rms value will be > 0.0. Can anyone suggest a way to weight down the observed difference to take this problem into account. Lets assume as a simplification that the F is distributed with a normal distribution with known Sigma, and that the 2 measurements , FP and FPH or F(+) and F(-) are independent.. I think that this means that the abs(difference) will follow a Poisson distribution, but I am not sure how to use the associated error tables. No prizes for the best answer, but it will improve the behaviour of many programs, difference pattersons and Ecalc in particular! Eleanor Dodson -- ------------------------------------------------------------------ Eleanor J.Dodson, Chemistry Department, University of York, U.K. Tel: Home +44 (1904) 42 44 49, work: +44 (1904) 43 25 65 ------------------------------------------------------------------

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