REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers

Cryo-EM particle identification from micrographs ("picking") is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms ("pickers") identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers. We frame consensus particle picking as a graph problem, which REPIC solves using integer linear programming. REPIC picks high-quality particles even when the best picker is not known a priori or a protein is difficult-to-pick (e.g., NOMPC ion channel). Reconstructions using consensus particles without particle filtering achieve resolutions comparable to those from particles picked by experts. Our results show that REPIC requires minimal (often no) manual intervention, and considerably reduces the burden on cryo-EM users for picker selection and particle picking. Availability: https://github.com/ccameron/REPIC .

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Publication Details

Journal
Communications Biology
Published
2024-10-31
DOI
https://doi.org/10.1038/s42003-024-07045-0
Citations
3
Primary Topic
Advanced Electron Microscopy Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.57

Funders

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article

REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers

Christopher J. F. Cameron, Hemant D. Tagare, Sebastian JH Seager, Mark Gerstein et al.
3 citations
Communications Biology
Advanced Electron Microscopy Techniques and Applications
1.57
article

REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers

Christopher J. F. Cameron, Hemant D. Tagare, Sebastian JH Seager, Mark Gerstein, Fred J. Sigworth
article en
3 citations

Abstract

Cryo-EM particle identification from micrographs ("picking") is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms ("pickers") identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers. We frame consensus particle picking as a graph problem, which REPIC solves using integer linear programming. REPIC picks high-quality particles even when the best picker is not known a priori or a protein is difficult-to-pick (e.g., NOMPC ion channel). Reconstructions using consensus particles without particle filtering achieve resolutions comparable to those from particles picked by experts. Our results show that REPIC requires minimal (often no) manual intervention, and considerably reduces the burden on cryo-EM users for picker selection and particle picking. Availability: https://github.com/ccameron/REPIC .

Communications BiologyVol. 7(1)
Yale University (US)
National Institutes of Health, National Institute of General Medical Sciences
Openalex Percentile: Top 12%
Advanced Electron Microscopy Techniques and Applications
1.57
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