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Super-sparse principal component analyses for high-throughput genomic data

BACKGROUND: Principal component analysis (PCA) has gained popularity as a method for the analysis of high-dimensional genomic data. However, it is often difficult to interpret the results because the principal components are linear combinations of all variables, and the coefficients (loadings) are t...

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Detalles Bibliográficos
Autores principales:	Lee, Donghwan, Lee, Woojoo, Lee, Youngjo, Pawitan, Yudi
Formato:	Texto
Lenguaje:	English
Publicado:	BioMed Central 2010
Materias:	Research article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2902448/ https://www.ncbi.nlm.nih.gov/pubmed/20525176 http://dx.doi.org/10.1186/1471-2105-11-296

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