# calcNhoodDistance: Calculate within neighbourhood distances In MikeDMorgan/miloR: Differential neighbourhood abundance testing on a graph

 calcNhoodDistance R Documentation

## Calculate within neighbourhood distances

### Description

This function will calculate Euclidean distances between single-cells in a neighbourhood using the same dimensionality as was used to construct the graph. This step follows the `makeNhoods` call to limit the number of distance calculations required.

### Usage

```calcNhoodDistance(x, d, reduced.dim = NULL, use.assay = "logcounts")
```

### Arguments

 `x` A `Milo` object with a valid `graph` slot. If `reduced.dims` is not provided and there is no valid populated `reducedDim` slot in `x`, then this is computed first with `d + 1` principal components. `d` The number of dimensions to use for computing within-neighbourhood distances. This should be the same value used construct the `graph`. `reduced.dim` If x is an `Milo` object, a character indicating the name of the `reducedDim` slot in the `Milo` object to use as (default: 'PCA'). Otherwise this should be an N X P matrix with rows in the same order as the columns of the input Milo object `x`. `use.assay` A character scalar defining which `assay` slot in the `Milo` to use

### Value

A `Milo` object with the distance slots populated.

### Author(s)

Mike Morgan, Emma Dann

### Examples

```library(SingleCellExperiment)
ux <- matrix(rpois(12000, 5), ncol=200)
vx <- log2(ux + 1)
pca <- prcomp(t(vx))

sce <- SingleCellExperiment(assays=list(counts=ux, logcounts=vx),
reducedDims=SimpleList(PCA=pca\$x))

milo <- Milo(sce)
milo <- buildGraph(milo, d=30, transposed=TRUE)
milo <- makeNhoods(milo)
milo <- calcNhoodDistance(milo, d=30)

milo
```

MikeDMorgan/miloR documentation built on Aug. 7, 2022, 8:21 a.m.