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MassDash:用于数据非依赖性采集质谱可视化的基于 Web 的仪表板。

MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization.

机构信息

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.

Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada.

出版信息

J Proteome Res. 2024 Jun 7;23(6):2306-2314. doi: 10.1021/acs.jproteome.4c00026. Epub 2024 Apr 29.

Abstract

With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, /, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.

摘要

随着越来越多的方法和仪器被应用于分析数据非依赖采集(DIA)数据,可视化对于验证自动化软件结果变得越来越重要。这里我们介绍 MassDash,这是一个跨平台的 DIA 质谱可视化和验证软件,用于比较各种流行工具的特征和结果。MassDash 提供了一个基于网络的界面和 Python 包,用于在多个自动化 DIA 特征检测工具之间进行交互式特征可视化和摘要报告绘图,包括 OpenSwath、DIA-NN 和 dreamDIA。此外,MassDash 实时处理肽段,能够在个人计算机上同时交互式可视化数十个运行的肽段。MassDash 支持各种多维可视化,包括保留时间、离子淌度、/ 和强度,为数据提供了更多的见解。模块化框架易于扩展,能够快速开发新的峰提取技术的算法,例如基于深度学习的方法和对现有工具的改进。MassDash 在 BSD 3-Clause 许可证下是开源的,可以在 https://github.com/Roestlab/massdash 上免费获得,并且可以在 https://massdash.streamlit.app 上访问演示版本。

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