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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Detalles Bibliográficos
Autores principales: Wanichthanarak, Kwanjeera, Jeamsripong, Saharuetai, Pornputtapong, Natapol, Khoomrung, Sakda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Research Article
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

Internet

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

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