# NOT RUN {
## compute a k-mer distance matrix for the woodmouse
## dataset (ape package) using a k-mer size of 5
library(ape)
data(woodmouse)
### subset global alignment by removing gappy ends
woodmouse <- woodmouse[, apply(woodmouse, 2, function(v) !any(v == 0xf0))]
### compute the distance matrix
woodmouse.dist <- kdistance(woodmouse, k = 5)
### cluster and plot UPGMA tree
woodmouse.tree <- as.dendrogram(hclust(woodmouse.dist, "average"))
plot(woodmouse.tree)
# }
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