Detection of inborn errors of metabolism utilizing GC-MS urinary metabolomics coupled with a modified orthogonal partial least squares discriminant analysis

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• 作者：Qin Yang^a ; ^b ; Shan-Shan Lin^c ; Jiang-Tao Yang^c ; ^{Yangjiangtao@aonelab.com.cn} ; Li-Juan Tang^a ; Ru-Qin Yu^a ; ^{rqyu@hnu.edu.cn}
• 关键词：Gas chromatography-mass spectrometry ; Urinary metabolomic analysis ; Inborn errors of metabolism ; Orthogonal partial least squares discriminant analysis ; Hybrid particle swarm optimization
• 刊名：Talanta
• 出版年：2017
• 出版时间：1 April 2017
• 年：2017
• 卷：165
• 期：Complete
• 页码：545-552
• 全文大小：1485 K
• 卷排序：165

文摘

Urinary metabolomic analysis based on GC-MS was used to detect IEMs. HPSO was employed to adaptively configure OPLS-DA forming HPSO-OPLSDA. HPSO-OPLSDA was performed on GC-MS dataset of IEMs with promising results. A noninvasive, feasible, and cost-effective metabolome analysis of IEMs was developed.