buildGraph: Build a k-nearest neighbour graph

In MikeDMorgan/miloR: Differential neighbourhood abundance testing on a graph

Build a k-nearest neighbour graph

Description

This function is borrowed from the old buildKNNGraph function in scran. Instead of returning an igraph object it populates the graph and distance slots in a Milo object. If the input is a SingleCellExperiment object or a matrix then it will return a de novo Milo object with the same slots filled.

Usage

buildGraph(
  x,
  k = 10,
  d = 50,
  transposed = FALSE,
  get.distance = FALSE,
  reduced.dim = "PCA",
  BNPARAM = KmknnParam(),
  BSPARAM = bsparam(),
  BPPARAM = SerialParam()
)

Arguments

x	A matrix, SingleCellExperiment or Milo object containing feature X cell gene expression data.
k	An integer scalar that specifies the number of nearest-neighbours to consider for the graph building.
d	The number of dimensions to use if the input is a matrix of cells X reduced dimensions. If this is provided, transposed should also be set=TRUE.
transposed	Logical if the input x is transposed with rows as cells.
get.distance	A logical scalar whether to compute distances during graph construction.
reduced.dim	A character scalar that refers to a specific entry in the reduceDim slot of the Milo object.
BNPARAM	refer to buildKNNGraph for details.
BSPARAM	refer to buildKNNGraph for details.
BPPARAM	refer to buildKNNGraph for details.

Details

This function computes a k-nearest neighbour graph. Each graph vertex is a single-cell connected by the edges between its neighbours. Whilst a kNN-graph is strictly directed, we remove directionality by forcing all edge weights to 1; this behaviour can be overriden by providing directed=TRUE.

If you wish to use an alternative graph structure, such as a shared-NN graph I recommend you construct this separately and add to the relevant slot in the Milo object.

Value

A Milo object with the graph and distance slots populated.

Author(s)

Mike Morgan, with KNN code written by Aaron Lun & Jonathan Griffiths.

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

MikeDMorgan/miloR documentation built on Feb. 29, 2024, 6:20 p.m.