Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data
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- 作者：Anna C. Reisetter ; Michael J. Muehlbauer ; James R. Bain…
- 关键词：Metabolomics ; Non ; targeted ; Gas chromatography/mass spectrometry ; GC/MS ; Normalization ; Batch effects
- 刊名：BMC Bioinformatics
- 出版年：2017
- 出版时间：December 2017
- 年：2017
- 卷：18
- 期：1
- 全文大小：2101KB
- 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
- 出版者：BioMed Central
- ISSN：1471-2105
- 卷排序：18
文摘
BackgroundMetabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds.