A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis

Highlights: Developed a data preprocessing strategy to cope with missing values and mask effects in data analysis from high variation of abundant metabolites. A new method- ‘x-VAST’ was developed to amend the measurement deviation enlargement. Applying the above strategy, several low abundant masked...

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Detalles Bibliográficos
Autores principales: Yang, Jun, Zhao, Xinjie, Lu, Xin, Lin, Xiaohui, Xu, Guowang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Molecular Biosciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4428451/
https://www.ncbi.nlm.nih.gov/pubmed/25988172
http://dx.doi.org/10.3389/fmolb.2015.00004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4428451/
https://www.ncbi.nlm.nih.gov/pubmed/25988172
http://dx.doi.org/10.3389/fmolb.2015.00004

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