Description Usage Arguments Note Examples
Given a correlation matrix and a vector of cluster assignments, plots squares around clusters of at least 2 sites.
1 | plot.cor.clusts(cor.mat, clusts, erase.non.clust = F, lwd = 2, main = "", xlab = "", labels = NULL)
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cor.mat |
An (m by m) correlation matrix |
clusts |
An $m$ vector of clusters assignments, as output by Acluster function. |
erase.non.clust |
If TRUE, do not present correlations between sites that are not in the same cluster (i.e. they are just white). Default is FALSE. |
lwd |
The width of the lines marking the clusters |
main |
Main title of the plot |
xlab |
Label of the X-axis |
labels |
Labels of the sites |
A plot is shown
1 2 3 4 5 6 7 | data(betas.7)
data(annot.7)
dat.7.ord <- order.betas.by.chrom.location(betas.7, annot = annot.7)
cluster.vec <- Acluster(ordr.vec = dat.7.ord$betas.by.chrom[[1]], thresh.dist = 0.5, location.vec = dat.7.ord$sites.locations.by.chrom[[1]]$Coordinate_37, max.dist = 1000, type = "single")
c.mat <- cor(t(betas.7)[,1:15], method = "spearman")
plot.cor.clusts(cor.mat = c.mat, clusts = cluster.vec[1:15])
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