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Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity. | LitMetric

AI Article Synopsis

  • Metabolomics focuses on analyzing metabolites in biological systems using techniques like NMR and HPLC/MS, but handling large data sets for metabolic fingerprinting is challenging.
  • Multivariate analysis is key for identifying metabolic biomarkers, yet the local false discovery rate (LFDR) is infrequently used in this context despite its potential for reliable insight.
  • In this study, LFDR effectively identified significant metabolites in rat urine related to hepatotoxicity from Genkwa flos treatment, outperforming traditional methods like principal component analysis (PCA).

Article Abstract

Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR) and HPLC/MS (high-performance liquid chromatography with mass spectrometry). Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR) is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF) treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA), LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3699555PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0067451PLOS

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