I vaguely recall an email from Kay Diderich about 3 years ago to this board but I couldn't find it, describing a neat method of distorting the diffraction image to meet the ellipsoidal characteristics of the anisotropic diffraction. But I might be confusion myself, anyhow Kay can you comment on this ? I think it involved a feature in Sharp which I never used.
Jürgen - Jürgen Bosch Johns Hopkins Bloomberg School of Public Health Department of Biochemistry & Molecular Biology Johns Hopkins Malaria Research Institute 615 North Wolfe Street, W8708 Baltimore, MD 21205 Phone: +1-410-614-4742 Lab: +1-410-614-4894 Fax: +1-410-955-3655 http://web.mac.com/bosch_lab/<http://web.me.com/bosch_lab/> On Jun 9, 2010, at 11:49 AM, James Holton wrote: Frederic VELLIEUX wrote: Anisotropy in the diffraction pattern could simply be due to the shape of the crystals. The intensity of diffraction is a function of the volume of diffracting matter that is hit by the X-ray beam. Think for example of a thin plate crystal, which you rotate in the X-ray beam. When the plate is perpendicular to the X-ray beam, the volume of matter hit by the X-rays is much smaller than when the plate is parallel to the X-ray beam. Fred, I think this is a bit misleading. Although diffraction anisotropy is often accompanied by platy or needle-y crystals, the crystal shape is neither necessary nor sufficient to produce an anisotropic B factor. You will get an anisotropic SCALE factor if bits of the crystal are moving in and out of the beam as you describe, but scale factors and B factors are not the same thing! B factors arise from differences between neighboring unit cells (within a few microns of each other), and anisotropic B factors arise when the average displacement of atoms from their ideal lattice points is higher in one direction than another. Admittedly, both scale and B can have an effect on the resolution limit, but the latter kills high-angle spots much more rapidly than the former. Operationally, I recommend treating anisotropic data just like isotropic data. There is nothing wrong with measuring a lot of zeros (think about systematic absences), other than making irrelevant statistics like Rmerge higher. One need only glance at the formula for any R factor to see that it is undefined when the "true" F is zero. Unfortunately, there are still a lot of reviewers out there who were trained that "the Rmerge in the outermost resolution bin must be 20%", and so some very sophisticated ellipsoidal cut-off programs have been written to try and meet this criterion without throwing away good data. I am actually not sure where this idea came from, but I challenge anyone to come up with a sound statistical basis for it. Better to use I/sigma(I) as a guide, as it really does tell you how much "information vs noise" you have at a given resolution. -James Holton MAD Scientist
