4.4 Article

UltraMassExplorer: a browser-based application for the evaluation of high-resolution mass spectrometric data

期刊

RAPID COMMUNICATIONS IN MASS SPECTROMETRY
卷 33, 期 2, 页码 193-202

出版社

WILEY
DOI: 10.1002/rcm.8315

关键词

-

资金

  1. Alfred-Wegener-Institute Helmholtz Centre for Polar and Marine Research (AWI)

向作者/读者索取更多资源

Rationale High-resolution mass spectrometry (HRMS) with high sample throughput has become an important analytical tool for the analysis of highly complex samples and data processing has become a major challenge for the user community. Evaluating direct-infusion HRMS data without automated tools for batch processing can be a time-consuming step in the analytical pipeline. Therefore, we developed a new browser-based software tool for processing HRMS data. Methods The software, named UltraMassExplorer (UME), was written in the R programming language using the shiny library to build the graphical user interface. The performance of the integrated formula library search algorithm was tested using HRMS data derived from analyses of up to 50 extracts of marine dissolved organic matter. Results The software supports the processing of lists of calibrated masses of neutral, protonated or deprotonated molecules, with masses of up to 700 Da and a mass accuracy <3 ppm. In the performance test, the number of assigned peaks per second increased with the number of submitted peaks and reached a maximum rate of 4745 assigned peaks per second. Conclusions UME offers a complete data evaluation pipeline comprising a fast molecular formula assignment algorithm allowing for the swift reanalysis of complete datasets, advanced filter functions and the export of data, metadata and publication-quality graphics. Unique to UME is a fast and interactive connection between data and their visual representation. UME provides a new platform enabling an increased transparency, customization, documentation and comparability of datasets.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据