Load a comparison matrix into R
sourmash_comp_matrix <- read.csv("ecoli.cmp.csv")
# Label the rows
rownames(sourmash_comp_matrix) <- colnames(sourmash_comp_matrix)
# Transform for plotting
sourmash_comp_matrix <- as.matrix(sourmash_comp_matrix)
Make an MDS plot
fit <- dist(sourmash_comp_matrix)
fit <- cmdscale(fit)
x <- fit[, 1]
y <- fit[, 2]
plot(fit[ , 1], fit[ , 2], xlab = "Dimension 1", ylab = "Dimension 2")
Make a tSNE plot
library(Rtsne)
tsne_model <- Rtsne(sourmash_comp_matrix, check_duplicates=FALSE, pca=TRUE, perplexity=5, theta=0.5, dims=2)
d_tsne = as.data.frame(tsne_model$Y)
plot(d_tsne$V1, d_tsne$V2)
Make an unclustered heatmap
heatmap(sourmash_comp_matrix, Colv=F, scale='none')
Make a clustered heatmap
hc.rows <- hclust(dist(sourmash_comp_matrix))
hc.cols <- hclust(dist(t(sourmash_comp_matrix)))
heatmap(sourmash_comp_matrix[cutree(hc.rows,k=2)==1,], Colv=as.dendrogram(hc.cols), scale='none')