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Publication Detail

Title: ADAP-GC 3.2: Graphical Software Tool for Efficient Spectral Deconvolution of Gas Chromatography-High-Resolution Mass Spectrometry Metabolomics Data.

Authors: Smirnov, Aleksandr; Jia, Wei; Walker, Douglas I; Jones, Dean P; Du, Xiuxia

Published In J Proteome Res, (2018 01 05)

Abstract: ADAP-GC is an automated computational workflow for extracting metabolite information from raw, untargeted gas chromatography-mass spectrometry metabolomics data. Deconvolution of coeluting analytes is a critical step in the workflow, and the underlying algorithm is able to extract fragmentation mass spectra of coeluting analytes with high accuracy. However, its latest version ADAP-GC 3.0 was not user-friendly. To make ADAP-GC easier to use, we have developed ADAP-GC 3.2 and describe here the improvements on three aspects. First, all of the algorithms in ADAP-GC 3.0 written in R have been replaced by their analogues in Java and incorporated into MZmine 2 to make the workflow user-friendly. Second, the clustering algorithm DBSCAN has replaced the original hierarchical clustering to allow faster spectral deconvolution. Finally, algorithms originally developed for constructing extracted ion chromatograms (EICs) and detecting EIC peaks from LC-MS data are incorporated into the ADAP-GC workflow, allowing the latter to process high mass resolution data. Performance of ADAP-GC 3.2 has been evaluated using unit mass resolution data from standard-mixture and urine samples. The identification and quantitation results were compared with those produced by ADAP-GC 3.0, AMDIS, AnalyzerPro, and ChromaTOF. Identification results for high mass resolution data derived from standard-mixture samples are presented as well.

PubMed ID: 29076734 Exiting the NIEHS site

MeSH Terms: Algorithms; Cluster Analysis; Gas Chromatography-Mass Spectrometry/methods*; Information Storage and Retrieval; Metabolomics/methods*; Software*; Workflow

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