NBLAST Clustering"


Install the package if required

install.packages('nat.nblast', dependencies = TRUE)

Load the package and set up for knitr / 3D snapshot figures


Clustering with NBLAST scores

All by all scores

First we create a 20 x 20 NBLAST all by all score matrix for 20 Kenyon cells included with the nat package

kcscores <- nblast_allbyall(kcs20)


Hierarchically cluster the Kenyon scores and divide the clustering into 3 groups

hckcs <- nhclust(scoremat=kcscores)
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

3D plot

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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nat.nblast documentation built on Jan. 23, 2020, 5:06 p.m.