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目的:采用磁共振( magnetic resonance, MR)波谱技术测试不同性别大鼠尿液代谢物并用不同标准化方法进行预处理,探讨不同标准化方法对分析结果的影响。方法:大鼠尿液MR图谱数据经过中心化( mean-centering and not scaling,Ctr)和自动规格化(unit variance scaling,UV)两种不同标准化方法处理后用正交偏最小二乘判别分析(orthogonal to partial least squares discriminant analysis,OPLS-DA)法分析,通过相关系数的计算确定不同性别大鼠尿液中含量有差异的代谢物。结果:数据进行中心化处理后判别出两组大鼠尿液中缬氨酸、乙酸、鸟氨酸、氨基马尿酸、苯乙胺、氧氨嘧啶、甲胺、二甲胺、尿囊素、延胡索酸、丙氨酸、柠檬酸和化学位移在δ4.14的一种未知代谢物等13种代谢物含量有差异。进行自动规格化处理后,判别出以上除柠檬酸外的12种代谢物以及硫胺、肌酸酐、甲酸和化学位移在δ2.92的一种未知代谢物等4种代谢物含量有差异。结论:自动规格化处理是代谢组学研究中比较灵敏的数据预处理手段。
OBJECTIVE: To test urinary metabolites of different sexes by magnetic resonance (MR) spectroscopy and to pretreat them with different standardized methods to explore the influence of different standardization methods on the analysis results. Methods: The MR data of urine of rats were processed by two different normalization methods of mean-centering and not scaling (Ctr) and unit variance scaling (UV). The data were analyzed by orthogonal partial least squares discriminant analysis OPLS-DA) method was used to determine the metabolites in the urine of different sexes. Results: The data of central processing identified two groups of rats urine valine, acetic acid, ornithine, amino hippuric acid, phenethylamine, oxyntamic acid, methylamine, dimethylamine, allantoin, Fumaric acid, alanine, citric acid and chemical shifts in a δ.14.14 unknown metabolites and other 13 metabolites content differences. After the automatic normalization process, the above four metabolites except citric acid and thiamine, creatinine and formic acid and an unknown metabolite with a chemical shift of δ2.92 were identified. Conclusion: Automated normalization is a sensitive data preprocessing method in metabolomics research.