Creation of Libraries of Recurring Mass Spectra from Large Data Sets Assisted by a Dual-Column Workflow

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• 作者：W. Gary Mallard ; N. Rabe Andriamaharavo ; Yuri A. Mirokhin ; John M. Halket ; Stephen E. Stein
• 刊名：Analytical Chemistry
• 出版年：2014
• 出版时间：October 21, 2014
• 年：2014
• 卷：86
• 期：20
• 页码：10231-10238
• 全文大小：423K
• ISSN：1520-6882

文摘

An analytical methodology has been developed for extracting recurrent unidentified spectra (RUS) from large GC/MS data sets. Spectra were first extracted from original data files by the Automated Mass Spectral Deconvolution and Identification System (AMDIS; Stein, S. E. J. Am. Soc. Mass Spectrom. 1999, 10, 770鈥?/x>781) using settings designed to minimize spurious spectra, followed by searching the NIST library with all unidentified spectra. The spectra that could not be identified were then filtered to remove poorly deconvoluted data and clustered. The results were assumed to be unidentified components. This was tested by requiring each unidentified spectrum to be found in two chromatographic columns with slightly different stationary phases. This methodology has been applied to a large set of pediatric urine samples. A library of spectra and retention indices for derivatized urine components, both identified and recurrent unidentified, has been created and is available for download.