A hierarchical approach to removal of unwanted variation for large-scale metabolomics data

Liquid chromatography-mass spectrometry-based metabolomics studies are increasingly applied to large population cohorts, which run for several weeks or even years in data acquisition. This inevitably introduces unwanted intra- and inter-batch variations over time that can overshadow true biological...

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Detalles Bibliográficos
Autores principales: Kim, Taiyun, Tang, Owen, Vernon, Stephen T., Kott, Katharine A., Koay, Yen Chin, Park, John, James, David E., Grieve, Stuart M., Speed, Terence P., Yang, Pengyi, Figtree, Gemma A., O’Sullivan, John F., Yang, Jean Yee Hwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371158/
https://www.ncbi.nlm.nih.gov/pubmed/34404777
http://dx.doi.org/10.1038/s41467-021-25210-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371158/
https://www.ncbi.nlm.nih.gov/pubmed/34404777
http://dx.doi.org/10.1038/s41467-021-25210-5

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