Semi-supervised adaptive-height snipping of the hierarchical clustering tree

BACKGROUND: In genomics, hierarchical clustering (HC) is a popular method for grouping similar samples based on a distance measure. HC algorithms do not actually create clusters, but compute a hierarchical representation of the data set. Usually, a fixed height on the HC tree is used, and each conti...

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Detalles Bibliográficos
Autores principales: Obulkasim, Askar, Meijer, Gerrit A, van de Wiel, Mark A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302100/
https://www.ncbi.nlm.nih.gov/pubmed/25592847
http://dx.doi.org/10.1186/s12859-014-0448-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302100/
https://www.ncbi.nlm.nih.gov/pubmed/25592847
http://dx.doi.org/10.1186/s12859-014-0448-1

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