评估 BAYESIL 在使用有限样本量的情况下对 H NMR 数据进行自动注释的效果：在非洲象血清中的应用。
Evaluation of BAYESIL for automated annotation of H NMR data using limited sample volumes: application to African elephant serum.
机构信息
Centre for Human Metabolomics, North-West University, Potchefstroom, South Africa.
Department of Microbiology and Biochemistry, University of the Free State, Bloemfontein, South Africa.
出版信息
Metabolomics. 2023 Mar 30;19(4):31. doi: 10.1007/s11306-023-02001-1.
INTRODUCTION
Technological advancements enabled the analyses of limited sample volumes on H NMR. Manual spectral profiling of the data is, however, complex, and timely.
OBJECTIVE
To evaluate the performance of BAYESIL for automated identification and quantification of H NMR spectra of limited volume samples.
METHOD
Aliquots of a pooled African elephant serum sample were analyzed using standard and reduced volumes. Performance was evaluated on confidence scores, non-detects and laboratory CV.
RESULTS
Of the 47 compounds detected, 28 had favorable performances. The approach could differentiate samples based on biological variation.
CONCLUSIONS
BAYESIL is valuable for limited sample H NMR data analyses.
简介
技术进步使得对 H NMR 的有限样本量进行分析成为可能。然而，手动对数据进行光谱分析非常复杂且耗时。
目的
评估 BAYESIL 在自动识别和定量有限体积样本的 H NMR 光谱方面的性能。
方法
使用标准和减少的体积分析 pooled African elephant serum 样本的等分试样。性能评估基于置信分数、未检出和实验室 CV。
结果
在所检测的 47 种化合物中，有 28 种具有良好的性能。该方法可以基于生物变异性来区分样本。
结论
BAYESIL 对有限样本量的 H NMR 数据分析很有价值。
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