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一个用于 RELION 元数据可视化的基于网络的仪表板。

A web-based dashboard for RELION metadata visualization.

机构信息

Spanish National Cancer Research Centre (CNIO), Melchor Fernández Almagro 3, 28029 Madrid, Spain.

出版信息

Acta Crystallogr D Struct Biol. 2024 Feb 1;80(Pt 2):93-100. doi: 10.1107/S2059798323010902. Epub 2024 Jan 24.

Abstract

Cryo-electron microscopy (cryo-EM) has witnessed radical progress in the past decade, driven by developments in hardware and software. While current software packages include processing pipelines that simplify the image-processing workflow, they do not prioritize the in-depth analysis of crucial metadata, limiting troubleshooting for challenging data sets. The widely used RELION software package lacks a graphical native representation of the underlying metadata. Here, two web-based tools are introduced: relion_live.py, which offers real-time feedback on data collection, aiding swift decision-making during data acquisition, and relion_analyse.py, a graphical interface to represent RELION projects by plotting essential metadata including interactive data filtration and analysis. A useful script for estimating ice thickness and data quality during movie pre-processing is also presented. These tools empower researchers to analyse data efficiently and allow informed decisions during data collection and processing.

摘要

冷冻电子显微镜(cryo-EM)在过去十年中取得了重大进展,这得益于硬件和软件的发展。虽然当前的软件包包括简化图像处理工作流程的处理管道,但它们并没有优先考虑深入分析关键元数据,从而限制了对具有挑战性数据集的故障排除。广泛使用的 RELION 软件包缺乏对底层元数据的图形原生表示。在这里,引入了两个基于网络的工具:relion_live.py,它提供数据收集的实时反馈,在数据采集过程中帮助快速做出决策,以及 relion_analyse.py,它是一个图形界面,通过绘制包括交互式数据过滤和分析在内的基本元数据来表示 RELION 项目。还提供了一个用于在电影预处理过程中估计冰层厚度和数据质量的有用脚本。这些工具使研究人员能够高效地分析数据,并在数据收集和处理过程中做出明智的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2c8/10836394/6b003b12d5bf/d-80-00093-fig1.jpg

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