GOCluster: Circular dendrogram.
In GOplot: Visualization of Functional Analysis Data

Description Usage Arguments Details Examples

GOCluster generates a circular dendrogram of the data clustering using by default euclidean distance and average linkage.The inner ring displays the color coded logFC while the outside one encodes the assigned terms to each gene.

1 2	GOCluster(data, process, metric, clust, clust.by, nlfc, lfc.col, lfc.min, lfc.max, lfc.space, lfc.width, term.col, term.space, term.width)

`data`	A data frame which should be the result of `circle_dat` in case the data contains only one logFC column. Otherwise `data` is a data frame whereas the first column contains the genes, the second the term and the following columns the logFCs of the different contrasts.
`process`	A character vector of selected processes (ID or term description)
`metric`	A character vector specifying the distance measure to be used (default='euclidean'), see `dist`
`clust`	A character vector specifying the agglomeration method to be used (default='average'), see `hclust`
`clust.by`	A character vector specifying if the clustering should be done for gene expression pattern or functional categories. By default the clustering is done based on the functional categories.
`nlfc`	If TRUE `data` contains multiple logFC columns (default= FALSE)
`lfc.col`	Character vector to define the color scale for the logFC of the form c(high, midpoint,low)
`lfc.min`	Specifies the minimium value of the logFC scale (default = -3)
`lfc.max`	Specifies the maximum value of the logFC scale (default = 3)
`lfc.space`	The space between the leafs of the dendrogram and the ring for the logFC
`lfc.width`	The width of the logFC ring
`term.col`	A character vector specifying the colors of the term bands
`term.space`	The space between the logFC ring and the term ring
`term.width`	The width of the term ring

The inner ring can be split into smaller rings to display multiply logFC values resulting from various comparisons.

## Not run: 
#Load the included dataset
data(EC)

#Generating the circ object
circ<-circular_dat(EC$david, EC$genelist)

#Creating the cluster plot
GOCluster(circ, EC$process)

#Cluster the data according to gene expression and assigning a different color scale for the logFC
GOCluster(circ,EC$process,clust.by='logFC',lfc.col=c('darkgoldenrod1','black','cyan1'))

## End(Not run)