Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes

BACKGROUND: The increased multi-omics information on carefully phenotyped patients in studies of complex diseases requires novel methods for data integration. Unlike continuous intensity measurements from most omics data sets, phenome data contain clinical variables that are binary, ordinal and cate...

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Detalles Bibliográficos
Autores principales: Kim, SungHwan, Herazo-Maya, Jose D., Kang, Dongwan D., Juan-Guardela, Brenda M., Tedrow, John, Martinez, Fernando J., Sciurba, Frank C., Tseng, George C., Kaminski, Naftali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4642618/
https://www.ncbi.nlm.nih.gov/pubmed/26560100
http://dx.doi.org/10.1186/s12864-015-2170-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4642618/
https://www.ncbi.nlm.nih.gov/pubmed/26560100
http://dx.doi.org/10.1186/s12864-015-2170-4

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