getClusterRelatedness function

Hierarchichal Clustering of Link Communities

This function hierarchically clusters the link communities themselves and returns an object of class hclust.

getClusterRelatedness(x, clusterids = 1:x$numbers[3], hcmethod = "ward.D", 
        cluster = TRUE, plot = TRUE, cutat = NULL, col = TRUE, 
        pal = brewer.pal(11, "Spectral"), labels = FALSE, plotcut = TRUE, 
        right = TRUE, verbose = TRUE, ...)

Arguments

• x: An object of class linkcomm.
• clusterids: An integer vector of community IDs. Defaults to all communities.
• hcmethod: A character string naming the hierarchical clustering method to use. Can be one of "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid". Defaults to "ward.D".
• cluster: Logical, whether to cluster the communities. If FALSE, the function returns the upper triangular dissimilarity matrix as a vector. Defaults to TRUE.
• plot: Logical, whether to plot the cluster dendrogram.
• cutat: A numerical value at which to cut the dendrogram. If NULL, the dendrogram is not cut and meta-communities are not returned. Defaults to NULL.
• col: Logical, whether to colour the dendrogram. Defaults to TRUE.
• pal: A character vector describing a colour palette to be used for colouring the meta-communites in the dendrogram plot. Defaults to brewer.pal(11, "Spectral").
• labels: Logical, whether to add labels to the dendrogram plot.
• plotcut: Logical, whether to display a horizontal line where the dendrogram is cut. Defaults to TRUE.
• right: Logical, whether to orient the dendrogram to the right. Defaults to TRUE.
• verbose: Logical, whether to display the progress of the calculation on the screen. Defaults to TRUE.
• ...: Additional arguments to be passed to plot.

Details

Extracting meta-communities allows the user to explore community relatedness and structure at higher levels. Community relatedness is calculated using the Jaccard coefficient and the number of nodes that community i and j share:

Returns

Either a numerical vector (the upper triangular dissimilarity matrix - if cluster = FALSE), a list of integer vectors (the meta-communities - if cutat is not NULL), or an object of class hclust (if cluster is TRUE and cutat is NULL).

References

Kalinka, A.T. and Tomancak, P. (2011). linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics 27 , 2011-2012.

Author(s)

Alex T. Kalinka alex.t.kalinka@gmail.com

See Also

meta.communities, cutDendrogramAt, hclust

Examples

## Generate graph and extract link communities.
g <- swiss[,3:4]
lc <- getLinkCommunities(g)

## Cluster the link communities.
getClusterRelatedness(lc)

## Cluster the link communities, cut the dendrogram, and return the meta-communities.
getClusterRelatedness(lc, cutat = 1)