Better models by discarding data?

Diederichs, Kay; Karplus, P. Andrew

Better models by discarding data?

Dateien

Diederichs_263092.pdfGröße: 611.35 KBDownloads: 222

Datum

2013

Autor:innen

Diederichs, Kay

Karplus, P. Andrew

Open Access-Veröffentlichung

Open Access Hybrid

Sammlungen

Biologie

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Acta Crystallographica Section D : Biological Crystallography. 2013, 69(7), pp. 1215-1222. ISSN 0907-4449. eISSN 1399-0047. Available under: doi: 10.1107/S0907444913001121

Zusammenfassung

In macromolecular X-ray crystallography, typical data sets have substantial multiplicity. This can be used to calculate the consistency of repeated measurements and thereby assess data quality. Recently, the properties of a correlation coefficient, CC_1/2, that can be used for this purpose were characterized and it was shown that CC_1/2 has superior properties compared with "merging" R values. A derived quantity, CC*, links data and model quality. Using experimental data sets, the behaviour of CC_1/2 and the more conventional indicators were compared in two situations of practical importance: merging data sets from different crystals and selectively rejecting weak observations or (merged) unique reflections from a data set. In these situations controlled "paired-refinement" tests show that even though discarding the weaker data leads to improvements in the merging R values, the refined models based on these data are of lower quality. These results show the folly of such data-filtering practices aimed at improving the merging R values. Interestingly, in all of these tests CC_1/2 is the one data-quality indicator for which the behaviour accurately reflects which of the alternative data-handling strategies results in the best-quality refined model. Its properties in the presence of systematic error are documented and discussed.

Fachgebiet (DDC)

570 Biowissenschaften, Biologie

Schlagwörter

R value, correlation coefficient, data quality, model quality, outlier rejection

Zitieren

ISO 690

DIEDERICHS, Kay, P. Andrew KARPLUS, 2013. Better models by discarding data?. In: Acta Crystallographica Section D : Biological Crystallography. 2013, 69(7), pp. 1215-1222. ISSN 0907-4449. eISSN 1399-0047. Available under: doi: 10.1107/S0907444913001121

BibTex

@article{Diederichs2013-07Bette-26309,
  year={2013},
  doi={10.1107/S0907444913001121},
  title={Better models by discarding data?},
  number={7},
  volume={69},
  issn={0907-4449},
  journal={Acta Crystallographica Section D : Biological Crystallography},
  pages={1215--1222},
  author={Diederichs, Kay and Karplus, P. Andrew}
}

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Universitätsbibliographie

Ja