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

被引:0
|
作者
Cameron, Christopher J. F. [1 ,2 ]
Seager, Sebastian J. H. [1 ]
Sigworth, Fred J. [1 ,3 ,4 ]
Tagare, Hemant D. [2 ,4 ,5 ,6 ]
Gerstein, Mark B. [1 ,5 ,6 ,7 ,8 ]
机构
[1] Yale Univ, Dept Mol Biophys & Biochem, New Haven, CT 06520 USA
[2] Yale Univ, Dept Radiol & Biomed Imaging, New Haven, CT 06520 USA
[3] Yale Univ, Dept Cellular & Mol Physiol, New Haven, CT USA
[4] Yale Univ, Dept Biomed Engn, New Haven, CT USA
[5] Yale Univ, Program Computat Biol & Bioinformat, New Haven, CT 06520 USA
[6] Yale Univ, Dept Stat & Data Sci, New Haven, CT 06520 USA
[7] Yale Univ, Dept Comp Sci, New Haven, CT 06520 USA
[8] Yale Univ, Dept Biomed Informat & Data Sci, New Haven, CT 06520 USA
基金
美国国家卫生研究院;
关键词
ELECTRON; SELECTION; SYSTEM; DAMAGE;
D O I
10.1038/s42003-024-07045-0
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. Cryo-EM particle picking is difficult due to noise and no ground truth. Here, a computational method for finding consensus particles from different picking algorithms is presented. This method identifies high-quality particles with minimal user input.
引用
收藏
页数:12
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