Autoindexing diffraction images withiMosflm

Abstract

An overview of autoindexing diffraction images based on one-dimensional fast Fourier transforms is presented. The implementation of the algorithm in the Mosflm/iMosflm program suite is described with a discussion of practical issues that may arise and ways of assessing the success or failure of the procedure. Recent developments allow indexing of images that show multiple lattices, and several examples demonstrate the success of this approach in real cases.

The RpfC (Rv1884) atomic structure shows high structural conservation within the resuscitation-promoting factor catalytic domain

“…Default processing of data sets using either XDS (Kabsch, 2010) or iMosflm (Powell et al, 2013) always gave space group C222 1 . Data sets were reprocessed in P2 1 (Table 1) with care taken to use an R free selection that meant that all pseudoequivalent reflections were in the refined or the free data set.…”

New methods for indexing multi-lattice diffraction data

“…Very narrow wedges. It is widely recognized that the robustness of current indexing algorithms can be increased by using data from images that are widely separated in reciprocal space (for example, separated by a rotation of 90 ), particularly for more problematic cases (Steller et al, 1997;Powell et al, 2013;Winter et al, 2013). Therefore, this can make the indexing of multiple lattices from narrow wedges of data (e.g.…”

“…(a) Histogram of the fraction of overlapping pixels for the semi-synthetic six-lattice trypsin data set; (b) as for (a) but averaged across all data sets with the same number of lattices for two (red), three (green), four (blue) and six (cyan) crystals. methods, indexing was attempted with the recent implementation of multi-lattice indexing in iMosflm (Powell et al, 2013). When provided with the first 1 of images from the sixlattice data sets, iMosflm identified five lattices (only two of which had the correct unit cell) for one of the data sets and five lattices (only one of which had the correct unit cell) for the second data set.…”

“…Within MOSFLM (Leslie & Powell, 2007) it is now possible to index as many as four independent lattices (Powell et al, 2013); however, this requires the use of at least two images well spaced in rotation and may also require careful adjustment of parameters. For the multi-lattice indexing in LABELIT (Sauter & Poon, 2010) it is assumed that one main lattice may be assigned which identifies (by default) at least 40% of the reflections.…”

FELIX: an algorithm for indexing multiple crystallites in X-ray free-electron laser snapshot diffraction images

“…This approach has been shown to be effective to index up to six crystals when applied to wedge data (Powell et al, 2013;Gildea et al, 2014;Sauter & Poon, 2010). However, this presents a lesser challenge than the snapshot case, as the controlled rotation provides multiple views of the same group of crystals.…”