<p>A list that contains the GO annotations produced by getGeneSets of the <code>MLP</code> package for the genes in the geneMat data.</p>

datasets

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.

Marijke Van Moerbeke

IntClust

Integration of Multiple Data Sets with Clustering Techniques

GS function

<p>A data frame with 3 variables: ENTREZID, SYMBOL and GENENAME</p>

GS: List of GO Annotations

Description

Arguments

Format

Examples