Distribution based nearest neighbor imputation for truncated high dimensional data with applications to pre-clinical and clinical metabolomics studies

BACKGROUND: High throughput metabolomics makes it possible to measure the relative abundances of numerous metabolites in biological samples, which is useful to many areas of biomedical research. However, missing values (MVs) in metabolomics datasets are common and can arise due to both technical and...

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Detalles Bibliográficos
Autores principales: Shah, Jasmit S., Rai, Shesh N., DeFilippis, Andrew P., Hill, Bradford G., Bhatnagar, Aruni, Brock, Guy N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319174/
https://www.ncbi.nlm.nih.gov/pubmed/28219348
http://dx.doi.org/10.1186/s12859-017-1547-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319174/
https://www.ncbi.nlm.nih.gov/pubmed/28219348
http://dx.doi.org/10.1186/s12859-017-1547-6

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