Identification of rogue datasets in serial crystallography

Abstract

Advances in beamline optics, detectors and X-ray sources allow new techniques of crystallographic data collection. In serial crystallography, a large number of partial datasets from crystals of small volume are measured. Merging of datasets from different crystals in order to enhance data completeness and accuracy is only valid if the crystals are isomorphous, i.e. sufficiently similar in cell parameters, unit-cell contents and molecular structure. Identification and exclusion of non-isomorphous datasets is therefore indispensable and must be done by means of suitable indicators. To identify rogue datasets, the influence of each dataset on CC_1/2 [Karplus & Diederichs (2012 ▸). Science, 336, 1030-1033], the correlation coefficient between pairs of intensities averaged in two randomly assigned subsets of observations, is evaluated. The presented method employs a precise calculation of CC_1/2 that avoids the random assignment, and instead of using an overall CC_1/2, an average over resolution shells is employed to obtain sensible results. The selection procedure was verified by measuring the correlation of observed (merged) intensities and intensities calculated from a model. It is found that inclusion and merging of non-isomorphous datasets may bias the refined model towards those datasets, and measures to reduce this effect are suggested.

Keywords: CC1/2; isomorphism; model bias; non-isomorphism; outlier identification; precision; serial crystallography.

Figure 1

Histogram of ΔCC_{1/2_i} values for PepT. The −28.8σ unit outlier is indicated with an arrow.

Figure 2

Plot of ΔCC_{FOC_i} against ΔCC_{1/2_i} for PepT. The −28.8 8σ unit outlier (ΔCC_{1/2_i} ≃ −4.8 × 10⁻⁴) is boxed.

Figure 3

Histogram of ΔCC_{1/2_i} values for AlgE. The −14.8σ unit outlier is indicated with an arrow.

Figure 4

Plot of ΔCC_{FOC_i} against ΔCC_{1/2_i} for AlgE. Different colours and marker symbols refer to the different random shifts of the atom coordinates. Arrows indicate the change of ΔCC_{FOC_i} upon increasing the magnitude of random shifts for the three most significant outliers of the Gaussian distribution of Fig. 3 ▸.