A Computational Pipeline for LC-MS/MS Based Metabolite Identification

Bin Zhou, J. Xiao, H. Ressom
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引用次数: 3

Abstract

Metabolite identification is the major bottle-neck in LC-MS based metabolomic investigations. The mass-based search approach often leaves a large fraction of metabolites with either no identification or multiple putative identifications. As manual verification of metabolites is laborious, computational approaches are needed to obtain more reliable putative identifications and prioritize them. In this paper, a computational pipeline is proposed to assist metabolite identification with improved coverage and prioritization capability. The pipeline is based on multiple pieces of publicly-available software and databases. The proposed pipeline is successfully applied in an LC-MS/MS-based metabolomic study, where mass, retention time, and MS/MS spectrum were used to improve the accuracy of metabolite identification and to prioritize putative identifications for subsequent metabolite verification.
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基于LC-MS/MS的代谢物鉴定计算管道
代谢物鉴定是基于LC-MS的代谢组学研究的主要瓶颈。基于质量的搜索方法通常会留下很大一部分代谢物,要么没有鉴定,要么有多个假定的鉴定。由于代谢物的人工验证是费力的,需要计算方法来获得更可靠的推定鉴定并对它们进行优先排序。在本文中,提出了一个计算管道,以帮助代谢物鉴定提高覆盖率和优先级能力。该管道基于多个公开可用的软件和数据库。提议的管道已成功应用于基于LC-MS/MS的代谢组学研究,其中使用质量,保留时间和MS/MS谱来提高代谢物鉴定的准确性,并优先考虑后续代谢物验证的推定鉴定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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