Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework

BACKGROUND: In omics data integration studies, it is common, for a variety of reasons, for some individuals to not be present in all data tables. Missing row values are challenging to deal with because most statistical methods cannot be directly applied to incomplete datasets. To overcome this issue...

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Detalles Bibliográficos
Autores principales: Voillet, Valentin, Besse, Philippe, Liaubet, Laurence, San Cristobal, Magali, González, Ignacio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048483/
https://www.ncbi.nlm.nih.gov/pubmed/27716030
http://dx.doi.org/10.1186/s12859-016-1273-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048483/
https://www.ncbi.nlm.nih.gov/pubmed/27716030
http://dx.doi.org/10.1186/s12859-016-1273-5

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