TY - JOUR
T1 - A peak-finding algorithm based on robust statistical analysis in serial crystallography
AU - Hadian-Jazi, Marjan
AU - Messerschmidt, Marc
AU - Darmanin, Connie
AU - Giewekemeyer, Klaus
AU - Mancuso, Adrian P.
AU - Abbey, Brian
N1 - Publisher Copyright:
© International Union of Crystallography, 2017.
PY - 2017/12
Y1 - 2017/12
N2 - The recent development of serial crystallography at synchrotron and X-ray free-electron laser (XFEL) sources is producing crystallographic datasets of ever increasing volume. The size of these datasets is such that fast and efficient analysis presents a range of challenges that have to be overcome to enable real-time data analysis, which is essential for the effective management of XFEL experiments. Among the blocks which constitute the analysis pipeline, one major bottleneck is 'peak finding', whose goal is to identify the Bragg peaks within (often) noisy diffraction patterns. Development of faster and more reliable peak-finding algorithms will allow for efficient processing and storage of the incoming data, as well as the optimal use of diffraction data for structure determination. This paper addresses the problem of peak finding and, by extension, 'hit finding' in crystallographic XFEL datasets, by exploiting recent developments in robust statistical analysis. The approach described here involves two basic steps: (1) the identification of pixels which contain potential peaks and (2) modeling of the local background in the vicinity of these potential peaks. The presented framework can be generalized to include both complex background models and alternative models for the Bragg peaks.This manuscript addresses the problem of peak finding and, by extension, 'hit finding' in crystallographic X-ray free-electron laser datasets, by exploiting recent developments in robust statistical analysis.
AB - The recent development of serial crystallography at synchrotron and X-ray free-electron laser (XFEL) sources is producing crystallographic datasets of ever increasing volume. The size of these datasets is such that fast and efficient analysis presents a range of challenges that have to be overcome to enable real-time data analysis, which is essential for the effective management of XFEL experiments. Among the blocks which constitute the analysis pipeline, one major bottleneck is 'peak finding', whose goal is to identify the Bragg peaks within (often) noisy diffraction patterns. Development of faster and more reliable peak-finding algorithms will allow for efficient processing and storage of the incoming data, as well as the optimal use of diffraction data for structure determination. This paper addresses the problem of peak finding and, by extension, 'hit finding' in crystallographic XFEL datasets, by exploiting recent developments in robust statistical analysis. The approach described here involves two basic steps: (1) the identification of pixels which contain potential peaks and (2) modeling of the local background in the vicinity of these potential peaks. The presented framework can be generalized to include both complex background models and alternative models for the Bragg peaks.This manuscript addresses the problem of peak finding and, by extension, 'hit finding' in crystallographic X-ray free-electron laser datasets, by exploiting recent developments in robust statistical analysis.
KW - X-ray free-electron lasers (XFELs)
KW - peak finding
KW - robust statistics
KW - serial crystallography
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U2 - 10.1107/S1600576717014340
DO - 10.1107/S1600576717014340
M3 - Article
AN - SCOPUS:85037074457
SN - 0021-8898
VL - 50
SP - 1705
EP - 1715
JO - Journal of Applied Crystallography
JF - Journal of Applied Crystallography
IS - 6
ER -