FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation

Erney Ramírez-Aportela (), David Maluenda, Yunior C. Fonseca, Pablo Conesa, Roberto Marabini, J. Bernard Heymann, Jose Maria Carazo () and Carlos Oscar S. Sorzano ()
Additional contact information
Erney Ramírez-Aportela: Campus Univ. Autónoma de Madrid
David Maluenda: Campus Univ. Autónoma de Madrid
Yunior C. Fonseca: Campus Univ. Autónoma de Madrid
Pablo Conesa: Campus Univ. Autónoma de Madrid
Roberto Marabini: Campus Univ. Autónoma de Madrid
J. Bernard Heymann: NIH
Jose Maria Carazo: Campus Univ. Autónoma de Madrid
Carlos Oscar S. Sorzano: Campus Univ. Autónoma de Madrid

Nature Communications, 2021, vol. 12, issue 1, 1-7

Abstract: Abstract In recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure “FSC-Q”, and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-020-20295-w Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20295-w

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-20295-w

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().