CAPIU 0.2 – Clustering using A Priori Information via Unsupervised decision trees

CAPIU 0.2

:: DESCRIPTION

CAPIU is a novel approach for clustering samples (treatments, patients, condition etc) by using annotational information about the genes. The algorithm searches all pre-defined gene classes for classes that exhibit a strong clustering of the samples. These are then used to split the samples in two groups until no significant splits can be found. The result is visualized as a tree with gene classes as nodes and groups of samples as leaves.

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::DEVELOPER

Max Planck Institute for Molecular Plant Physiology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • R package
  • Biobase, MASS, mclust, e1071, cluster, hu6800, ellipse, GO.

:: DOWNLOAD

 CAPIU

:: MORE INFORMATION

Citation

Biom J. 2007 Apr;49(2):214-29.
Integrating functional knowledge during sample clustering for microarray data using unsupervised decision trees.
Redestig H, Repsilber D, Sohler F, Selbig J.