moranTest: Spatialy autocorrelation by Moran's I in C++

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

Spatialy autocorrelation by Moran's I in C++

Description

Spatialy autocorrelation by Moran's I in C++

Usage

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

Arguments

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

Value

Observed Moran's I statistic, the expected statistic under the null hypothesis of no spatial autocorrelation, the standard deviation under the null hypothesis, and p-value

Examples

data(mOB)
pos <- mOB$pos
weight <- getSpatialNeighbors(pos)
gexp <- normalizeCounts(mOB$counts, log=FALSE, verbose=FALSE)['Camk4',]
moranTest(gexp, weight)

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