Unsupervised reduction of random noise in complex data by a row-specific, sorted principal component-guided method

BACKGROUND: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but it tends to remove small features as well as random noise. RESULTS: We interpreted the PCs as a mere signal-rich coordina...

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Detalles Bibliográficos
Autores principales: Foley, Joseph W, Katagiri, Fumiaki
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2607290/
https://www.ncbi.nlm.nih.gov/pubmed/19040754
http://dx.doi.org/10.1186/1471-2105-9-508

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2607290/
https://www.ncbi.nlm.nih.gov/pubmed/19040754
http://dx.doi.org/10.1186/1471-2105-9-508

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