plotCluster: Plot cluster network

In haimbar/edgefinder: Detect Edges in Sparse Co-expression Graphs

Description

Plot a cluster network with all the nodes and edges - the central node is marked by a black circle. The radius of each point corresponds to its degree. The opacity corresponds to the percentage of edges from the node that is in the cluster (the darker it is, the larger the percentage of edges is within the cluster.) The distance from the center corresponds to the relative dissimilarity with the central node. This is computed as the number of neighbors the node and the central node do not have in common.

Usage

plotCluster(
  AdjMat,
  clustNo,
  clusterInfo = NULL,
  labels = FALSE,
  nodecol = "blue",
  labelsize = 1,
  figtitle = NULL,
  negcor = NULL,
  edgecols = "grey88"
)

Arguments

AdjMat	An adjacency Matrix (0/1).
clustNo	The chosen cluster.
clusterInfo	Obtained from graphComponents.
labels	If set to TRUE, show node names (default=FALSE).
nodecol	The color(s) of the nodes. Can be a single value or a vector of length equal to the number of rows in AdjMat
labelsize	Text size of node labels.
figtitle	The title of the plot (default=NULL).
negcor	The pairs which are negatively correlated, to be drawn as red edges (default=NULL). If set to null, all edges will have the same color.
edgecols	The colors to be used for edges. Default="grey88". If one value is given, all edges will be drawn using this color. If negcor is used to specify which edges are negatively correlated and edgecol contains two valid colors, the first is used for positive correlations, and the second for negative ones.

Examples

   data(WT)
   WTres <- edgefinder(WT, ttl = "Wild Type")
   WTComp <- graphComponents(WTres$AdjMat)
   plotCluster(WTres$AdjMat, 5, WTComp)
   # plotCluster(WTres$AdjMat, 5, WTComp, negcor = WTres$lt, edgecols = c("grey88","orange"))

haimbar/edgefinder documentation built on Dec. 20, 2021, 2:45 p.m.