Q2C: A software for managing mass spectrometry facilities

IF 2.8 2区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Diogo B. Lima , Max Ruwolt , Marlon D.M. Santos , Ke Pu , Fan Liu , Paulo C. Carvalho
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引用次数: 0

Abstract

We present Q2C, an open-source software designed to streamline mass spectrometer queue management and assess performance based on quality control metrics. Q2C provides a fast and user-friendly interface to visualize projects queues, manage analysis schedules and keep track of samples that were already processed. Our software includes analytical tools to ensure equipment calibration and provides comprehensive log documentation for machine maintenance, enhancing operational efficiency and reliability. Additionally, Q2C integrates with Google™ Cloud, allowing users to access and manage the software from different locations while keeping all data synchronized and seamlessly integrated across the system. For multi-user environments, Q2C implements a write-locking mechanism that checks for concurrent operations before saving data. When conflicts are detected, subsequent write requests are automatically queued to prevent data corruption, while the interface continuously refreshes to display the most current information from the cloud storage. Finally, Q2C, a demonstration video, and a user tutorial are freely available for academic use at https://github.com/diogobor/Q2C. Data are available from the ProteomeXchange consortium (identifier PXD055186).

Significance

Q2C addresses a critical gap in mass spectrometry facility management by unifying sample queue management with instrument performance monitoring. It ensures optimal instrument utilization, reduces turnaround times, and enhances data quality by dynamically prioritizing and routing samples based on analysis type and urgency. Unlike existing tools, Q2C integrates queue control and QC in a single platform, maximizing operational efficiency and reliability.

Abstract Image

Q2C:管理质谱设备的软件。
我们提出了Q2C,一个开源软件,旨在简化质谱仪队列管理和评估基于质量控制指标的性能。Q2C提供了一个快速和用户友好的界面来可视化项目队列,管理分析时间表和跟踪已经处理的样本。我们的软件包括分析工具,以确保设备校准,并为机器维护提供全面的日志文件,提高操作效率和可靠性。此外,Q2C与谷歌™云集成,允许用户从不同位置访问和管理软件,同时保持所有数据同步并在整个系统中无缝集成。对于多用户环境,Q2C实现了一种写锁定机制,在保存数据之前检查并发操作。当检测到冲突时,后续的写请求将自动排队,以防止数据损坏,同时界面不断刷新以显示来自云存储的最新信息。最后,Q2C,一个演示视频和一个用户教程可以在https://github.com/diogobor/Q2C上免费供学术使用。数据来自ProteomeXchange联盟(标识符PXD055186)。意义:Q2C通过将样品队列管理与仪器性能监测统一起来,解决了质谱设备管理中的一个关键空白。它确保了最佳的仪器利用率,减少了周转时间,并通过根据分析类型和紧急程度对样本进行动态优先排序和路由,提高了数据质量。与现有工具不同,Q2C将队列控制和QC集成在一个平台中,最大限度地提高了操作效率和可靠性。
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来源期刊
Journal of proteomics
Journal of proteomics 生物-生化研究方法
CiteScore
7.10
自引率
3.00%
发文量
227
审稿时长
73 days
期刊介绍: Journal of Proteomics is aimed at protein scientists and analytical chemists in the field of proteomics, biomarker discovery, protein analytics, plant proteomics, microbial and animal proteomics, human studies, tissue imaging by mass spectrometry, non-conventional and non-model organism proteomics, and protein bioinformatics. The journal welcomes papers in new and upcoming areas such as metabolomics, genomics, systems biology, toxicogenomics, pharmacoproteomics. Journal of Proteomics unifies both fundamental scientists and clinicians, and includes translational research. Suggestions for reviews, webinars and thematic issues are welcome.
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