代谢组学
脂类学
鉴定(生物学)
软件
化学
计算生物学
排名(信息检索)
计算机科学
数据挖掘
情报检索
色谱法
生物化学
植物
生物
程序设计语言
作者
Giuseppe Martano,Michele Leone,Pierluca D’Oro,Vittoria Matafora,Angela Cattaneo,Marco Masseroli,Angela Bachi
标识
DOI:10.1021/acs.analchem.0c00585
摘要
Metabolomics and lipidomics studies are becoming increasingly popular but available tools for automated data analysis are still limited. The major issue in untargeted metabolomics is linked to the lack of efficient ranking methods allowing accurate identification of metabolites. Herein, we provide a user-friendly open-source software, named SMfinder, for the robust identification and quantification of small molecules. The software introduces an MS2 false discovery rate approach, which is based on single spectral permutation and increases identification accuracy. SMfinder can be efficiently applied to shotgun and targeted analysis in metabolomics and lipidomics without requiring extensive in-house acquisition of standards as it provides accurate identification by using available MS2 libraries in instrument independent manner. The software, downloadable at www.ifom.eu/SMfinder, is suitable for untargeted, targeted, and flux analysis.
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