Install the package if required
install.packages('nat.nblast', dependencies = TRUE)
Load the package and set up for knitr / 3D snapshot figures
First we create a 20 x 20 NBLAST all by all score matrix for 20 Kenyon cells included with the nat package
library(nat) kcscores <- nblast_allbyall(kcs20)
Hierarchically cluster the Kenyon scores and divide the clustering into 3 groups
hckcs <- nhclust(scoremat=kcscores) library(dendroextras) dkcs <- colour_clusters(hckcs, k=3)
Plot a dendrogram of the clustering, with leaves labelled by true neuron type
labels(dkcs) <- with(kcs20[labels(dkcs)], type) par(cex=.7) # so labels are legible plot(dkcs)
You can create interactive 3D plots using the rgl package where different subgroups of neurons are coloured according to the calculated clustering.
plot3d(hckcs, k=3, db=kcs20, soma=T) par3d(userMatrix=diag(c(1,-1,-1,1), 4)) plot3d(MBL.surf, alpha=.1)
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