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How to plot dendrograms with large datasets?

开发者 https://www.devze.com 2023-04-04 09:08 出处:网络
I am using ape (Analysis of Phylogenetics and Evolution) package in R that has dendrogram drawing functionality. I use following commands to read the data in Newick format, and draw a dendrogram using

I am using ape (Analysis of Phylogenetics and Evolution) package in R that has dendrogram drawing functionality. I use following commands to read the data in Newick format, and draw a dendrogram using the plot function:

library("ape")
gcPhylo <-read.tree(file = "gc.tree")
plot(gcPhylo, show.node.label = TRUE)

As the data set is quite large, it is impossible to see any details in the lower levels of the tree. I can see just black areas but no details. I can only see few levels from the top, and then no detail.

I was开发者_运维问答 wondering if there is any zoom capability of the plot function. I tried to limit the area using xLim and yLim, however, they just limit the area, and do not zoom to make the details visible. Either zooming, or making the details visible without zooming will solve my problem.

I am also appreciated to know any other package, function, or tool that will help me overcoming the problem.

Thanks.


It is possible to cut a dendrogram at a specified height and plot the elements:

First create a clustering using the built-in dataset USArrests. Then convert to a dendrogram:

hc <- hclust(dist(USArrests))
hcd <- as.dendrogram(hc)

Next, use cut.dendrogram to cut at a specified height, in this case h=75. This produces a list of a dendrogram for the upper bit of the cut, and a list of dendograms, one for each branch below the cut:

par(mfrow=c(3,1))

plot(hcd, main="Main")
plot(cut(hcd, h=75)$upper, 
     main="Upper tree of cut at h=75")
plot(cut(hcd, h=75)$lower[[2]], 
     main="Second branch of lower tree with cut at h=75")

How to plot dendrograms with large datasets?


The cut function described in the other answer is a very good solution; if you would like to maintain the whole tree on one page for some interactive investigation you could also plot to a large page on a PDF.

The resulting PDF is vectorized so you can zoom in closely with your favourite PDF viewer without loss of resolution.

Here's an example of how to direct plot output to PDF:

# Open a PDF for plotting; units are inches by default
pdf("/path/to/a/pdf/file.pdf", width=40, height=15)

# Do some plotting
plot(gcPhylo)

# Close the PDF file's associated graphics device (necessary to finalize the output)
dev.off()
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