# nblast_allbyall

From nat.nblast v1.6.2
by James Manton

##### Wrapper function to compute all by all NBLAST scores for a set of neurons

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.

##### Usage

```
nblast_allbyall(x, ...)
"nblast_allbyall"(x, smat = NULL, db = getOption("nat.default.neuronlist"), ...)
"nblast_allbyall"(x, smat = NULL, distance = FALSE, normalisation = c("raw", "normalised", "mean"), ...)
```

##### Arguments

- x
- Input neurons (neuronlist or character vector)
- ...
- Additional arguments for methods or
`nblast`

- smat
- the scoring matrix to use (see details of
`nblast`

for meaning of default`NULL`

value) - db
- A neuronlist or a character vector naming one. Defaults to value of options("nat.default.neuronlist")
- distance
- logical indicating whether to return distances or scores.
- normalisation
- the type of normalisation procedure that should be
carried out, selected from
`'raw'`

,`'normalised'`

or`'mean'`

(i.e. the average of normalised scores in both directions). If`distance=TRUE`

then this cannot be raw.

##### Details

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.

##### TODO

It would be a good idea in the future to implement a parallel version of this function.

##### See Also

##### Examples

```
library(nat)
kcs20.scoremat=nblast_allbyall(kcs20)
kcs20.hclust=nhclust(scoremat=kcs20.scoremat)
plot(kcs20.hclust)
```

*Documentation reproduced from package nat.nblast, version 1.6.2, License: GPL-3*

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