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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Research Network of Computational and Structural Biotechnology
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6506811/ https://www.ncbi.nlm.nih.gov/pubmed/31110642 http://dx.doi.org/10.1016/j.csbj.2019.04.009 |