Integration of Multiple Data Sets with Clustering Techniques

Several integrative data methods in which information of objects from different data sources can be combined are included in the IntClust package. As a single data source is limited in its point of view, this provides more insight and the opportunity to investigate how the variables are interconnected. Clustering techniques are to be applied to the combined information. For now, only agglomerative hierarchical clustering is implemented. Further, differential gene expression and pathway analysis can be conducted on the clusters. Plotting functions are available to visualize and compare results of the different methods.


Reference manual

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0.1.0 by Marijke Van Moerbeke, a year ago

Browse source code at

Authors: Marijke Van Moerbeke

Documentation:   PDF Manual  

GPL-3 license

Imports ade4, a4Core, Biobase, cluster, plotrix, plyr, gplots, gridExtra, limma, gtools, e1071, pls, stats, utils, graphics, FactoMineR, analogue, lsa, SNFtool, grDevices, ggplot2, circlize, Rdpack, data.table, igraph

Suggests MLP, biomaRt,, a4Base

See at CRAN