nblast_allbyall | R Documentation |
Calls nblast
to compute the actual scores. Can accept
either a neuronlist
or neuron names as a character vector. This is a thin
wrapper around nblast
and its main advantage is the option of "mean"
normalisation for forward and reverse scores, which is the most sensible
input to give to a clustering algorithm as well as the choice of returning
a distance matrix.
nblast_allbyall(x, ...)
## S3 method for class 'character'
nblast_allbyall(x, smat = NULL, db = getOption("nat.default.neuronlist"), ...)
## S3 method for class 'neuronlist'
nblast_allbyall(
x,
smat = NULL,
distance = FALSE,
normalisation = c("raw", "normalised", "mean"),
...
)
x |
Input neurons ( |
... |
Additional arguments for methods or |
smat |
the scoring matrix to use (see details of |
db |
A |
distance |
logical indicating whether to return distances or scores. |
normalisation |
the type of normalisation procedure that should be
carried out, selected from |
Note that nat
already provides a function
nhclust
for clustering, which is a wrapper for R's
hclust
function. nhclust
actually expects raw scores
as input.
It would be a good idea in the future to implement a parallel version of this function.
nblast, sub_score_mat, nhclust
library(nat)
kcs20.scoremat=nblast_allbyall(kcs20)
kcs20.hclust=nhclust(scoremat=kcs20.scoremat)
plot(kcs20.hclust)
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