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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...
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| Publicado no: | Comput Struct Biotechnol J |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Research Network of Computational and Structural Biotechnology
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6506811/ https://ncbi.nlm.nih.gov/pubmed/31110642 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csbj.2019.04.009 |
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