signedLisa: Signed local indicators of spatial association to identify...

In JEFworks/MERingue: Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with non-uniform cellular densities

Signed local indicators of spatial association to identify regions driving global autocorrelation

Description

Signed local indicators of spatial association to identify regions driving global autocorrelation

Usage

signedLisa(x, weight, alternative = "greater")

Arguments

x	Feature value
weight	Adjacency weight matrix
alternative	"two.sided", "less", or "greater"

Value

Signed LISA statistic for each point

Examples

data(mOB)
pos <- mOB$pos
weight <- getSpatialNeighbors(pos)
gexp <- normalizeCounts(mOB$counts, log=FALSE, verbose=FALSE)['Camk4',]
plotEmbedding(pos, colors=gexp, cex=3)
slisa <- signedLisa(gexp, weight)
plotEmbedding(pos, colors=slisa, cex=3,
   gradientPalette=colorRampPalette(c('darkgreen', 'white', 'darkorange'))(100))

JEFworks/MERingue documentation built on June 11, 2022, 4:16 a.m.