通过共识进行可靠拾取(REPIC):利用多个冷冻电镜粒子拾取器的共识方法学

IF 5.2 1区 生物学 Q1 BIOLOGY Communications Biology Pub Date : 2024-10-31 DOI:10.1038/s42003-024-07045-0
Christopher J. F. Cameron, Sebastian J. H. Seager, Fred J. Sigworth, Hemant D. Tagare, Mark B. Gerstein
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引用次数: 0

摘要

从显微照片中识别低温电子显微镜颗粒("拾取")具有挑战性,因为信噪比低,而且缺乏颗粒位置的基本真相。最先进的计算算法("拾取器")能识别不同的颗粒集,这使得为感兴趣的蛋白质选择最合适的拾取器变得更加复杂。在这里,我们提出了 "通过共识进行可靠剔选"(REPIC),这是一种识别多个剔选器输出中共同粒子的计算方法。我们将共识粒子选取作为一个图问题,REPIC 使用整数线性规划来解决这个问题。即使事先不知道最佳拾取者或蛋白质难以拾取(如 NOMPC 离子通道),REPIC 也能拾取高质量的粒子。在不进行粒子过滤的情况下,使用共识粒子重建的分辨率可与专家挑选的粒子重建的分辨率相媲美。我们的研究结果表明,REPIC 只需要极少(通常不需要)的人工干预,大大减轻了低温电子显微镜用户在拾取器选择和粒子拾取方面的负担。可用性:https://github.com/ccameron/REPIC 。低温电子显微镜粒子拾取因噪声和无地面实况而困难重重。这里介绍了一种从不同拾取算法中寻找共识粒子的计算方法。该方法只需最少的用户输入即可识别高质量粒子。
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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 . 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.
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来源期刊
Communications Biology
Communications Biology Medicine-Medicine (miscellaneous)
CiteScore
8.60
自引率
1.70%
发文量
1233
审稿时长
13 weeks
期刊介绍: Communications Biology is an open access journal from Nature Research publishing high-quality research, reviews and commentary in all areas of the biological sciences. Research papers published by the journal represent significant advances bringing new biological insight to a specialized area of research.
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