CAPIU - Clustering using A Priori Information via Unsupervised decision trees

general

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.

availability

CAPIU is implemented both as an R package and on this page as a web service. Either download the package and follow examples in the R documentation files or click login below to start the upload process.

dependencies

R [tested with v2.4.0 on FC4 GNU/Linux]

Following packages are also needed: Biobase, MASS, mclust, e1071, cluster, hu6800, ellipse, GO, pcaMethods.dot, which is part of the Graphviz package.

documentation

CAPIU is described in the manuscript 'Integrating functional knowledge during sample clustering for microarray data using unsupervised decision trees' published in the Biometrical Journal.

contact

For questions, comments, bugs etc, please contact Henning Redestig.

downloads

program file: capiu_1.0.4.tar.gz

R documentation: capiu.pdf

Example upload file: example.csv (for Affymetrix chip hu6800)