Normalization method for metabolomics data using optimal selection of multiple internal standards |
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Authors: | Marko Sysi-Aho Mikko Katajamaa Laxman Yetukuri Matej Orešič |
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Affiliation: | 1.VTT Technical Research Centre of Finland,Espoo,Finland;2.Turku Centre for Biotechnology,Turku,Finland |
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Abstract: | Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. |
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