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Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree

Bioconductor version: 2.13

Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy.

Author: Askar Obulkasim

Maintainer: Askar Obulkasim <askar703 at>

Citation (from within R, enter citation("HCsnip")):


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PDF densityR.pdf
PDF entropy.pdf
PDF R Script HCsnip
PDF Rank.pdf
PDF   Reference Manual


biocViews Bioinformatics, Clustering, GeneExpression, Microarray, Software, aCGH
Version 1.2.0
In Bioconductor since BioC 2.12 (R-3.0)
License GPL (>= 2)
Depends R (>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase
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