calcNhoodExpression: Average expression within neighbourhoods

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

Average expression within neighbourhoods

Description

This function calculates the mean expression of each feature in the Milo object stored in the assays slot. Neighbourhood expression data are stored in a new slot nhoodExpression.

Usage

calcNhoodExpression(x, assay = "logcounts", subset.row = NULL, exprs = NULL)

Arguments

x	A Milo object with nhoods slot populated, alternatively a NxM indicator matrix of N cells and M nhoods.
assay	A character scalar that describes the assay slot to use for calculating neighbourhood expression.
subset.row	A logical, integer or character vector indicating the rows of x to use for sumamrizing over cells in neighbourhoods.
exprs	If x is a list of neighbourhoods, exprs is a matrix of genes X cells to use for calculating neighbourhood expression.

Details

This function computes the mean expression of each gene, subset by subset.rows where present, across the cells contained within each neighbourhood.

Value

A Milo object with the nhoodExpression slot populated.

Author(s)

Mike Morgan

Examples

require(SingleCellExperiment)
m <- matrix(rnorm(100000), ncol=100)
milo <- Milo(SingleCellExperiment(assays=list(logcounts=m)))
milo <- buildGraph(m, k=20, d=30)
milo <- makeNhoods(milo)
milo <- calcNhoodExpression(milo)
dim(nhoodExpression(milo))

MarioniLab/miloR documentation built on Oct. 18, 2024, 6:04 p.m.