Dear Experts,

I am using the below script to generate the heat map of gene expression
data. I am using Hierarchical Clustering (hclust) for clustering. Now I want
to compare different clustering parameters such as *K-means* clustering, Model
Based Clustering,

I have two queries:

1. How to incorporate different clustering method in the same code?
2. Is this possible to implement pvclust in the same code and cluster
accordingly?

library(gplots)

#===========Cyto=========
#x=read.table("Cyto_shoot.txt", header=TRUE)
mat=data.matrix(x)
heatmap.2(mat,
# c('red','green','orange','blue','yellow',
'gray','black','brown','aquamarine3','cyan',
'darkmagenta','darkviolet','green4'))
col=colorRampPalette(c("green","white","red"))(256),

#col=greenred(75),
#col = cm.colors(256),
#bgStyle="3D Rectangle",
#bgGradientMode=" Diagonal Edge",
Rowv=TRUE,

Colv=FALSE,
distfun = dist,
hclustfun = hclust,
dendrogram = c("row"),
scale = c("column"),
na.rm=TRUE,
trace="none",
sepwidth=c(0.05,0.05),
margins = c(03, 40),
xlab = "", ylab = "",
labRow = NULL,
labCol = NULL,
key=TRUE,
keysize=1,
density.info=c("none"),
)


Thanks in advance

Kamal

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