Accounting for biological variation with linear mixed-effects modelling improves the quality of clinical metabolomics data
Metabolite profiles from biological samples suffer from both technical variations and subject-specific variants. To improve the quality of metabolomics data, conventional data processing methods can be employed to remove technical variations. These methods do not consider sources of subject variatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S200103701930025X |