Milo implementation using graph based features for neighbourhood sampling and SpatialFDR

miloR_graph_refinement.R

library(miloR)

## Load dummy data
data(sim_trajectory)
milo.meta <- sim_trajectory$meta
milo.obj <- Milo(sim_trajectory$SCE)

## Build KNN graph neighbourhoods
milo.obj <- buildGraph(milo.obj, k=20, d=30)
milo.obj <- makeNhoods(milo.obj, k=20, d=30, refined=TRUE, prop=0.2, refinement_scheme="graph")

## Count cells in nhoods
milo.obj <- countCells(milo.obj, samples="Sample", meta.data=milo.meta)

## Test for differential abundance
milo.design <- as.data.frame(xtabs(~ Condition + Sample, data=milo.meta))
milo.design <- milo.design[milo.design$Freq > 0, ]
rownames(milo.design) <- milo.design$Sample
milo.design <- milo.design[colnames(nhoodCounts(milo.obj)),]
milo_res <- testNhoods(milo.obj, design=~Condition, design.df=milo.design, fdr.weighting="graph-overlap")