Correlation plots and bar plots to visualize four datasets in R

Question

I've got some scores post-ssGSEA score calculation into four data frames in r.

The data frame looks something like this:

dput(t_ssgsea_OPC[1:250,])

structure(list(Classical = c(0.170108215263314, 0.114886799846454, 
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), class = "data.frame")

I wish to visualize the data, but there are four such data frames and I wish to visualize them together, for that reason I thought four correlation plots will look good along with column plots, one for each of the four columns in four data frames resulting in sixteen columns.

I'm unable to come up with a good technique to visualize the data, any help will be helpful.

Also while trying the correlation plot:

ssgsea_cormat <- melt(t_ssgsea_OPC)
No id variables; using all as measure variables
Warning message:
In melt(t_ssgsea_OPC) :
  The melt generic in data.table has been passed a data.frame and will attempt to redirect to the relevant reshape2 method; please note that reshape2 is deprecated, and this redirection is now deprecated as well. To continue using melt methods from reshape2 while both libraries are attached, e.g. melt.list, you can prepend the namespace like reshape2::melt(t_ssgsea_OPC). In the next version, this warning will become an error.

I have no idea why this warning message is coming up, and the melted dataset doesn't have the row names and has just two columns. Any suggestions to help here will be welcomed too.

Answer 1

An option to visualize your data would be a heatmap. A lot of options are given in the heatmap.2 function, you can find out more here.

library(gplots)

heatmap.2(as.matrix(t_ssgsea_OPC),
          scale="column",
          Rowv=F, Colv=F, dendrogram="none", 
          breaks=seq(-1,1,0.01), col=redblue(200), trace="none",
          margins=c(9,8), srtCol = 30)

And admitting you have 16 columns (here just the same dataframe repeated 4 times):

t_ssgsea_OPC_16cols = cbind(t_ssgsea_OPC, rep(t_ssgsea_OPC[,1:4],3))

heatmap.2(as.matrix(t_ssgsea_OPC_16cols),
          scale="column",
          Rowv=F, Colv=F, dendrogram="none", 
          breaks=seq(-1,1,0.01), col=redblue(200), trace="none",
          margins=c(9,8), srtCol = 30)