AdjScoreGenes.internal: Use the Adjacency Score to evaluate colocalization of given...

In CamaraLab/STvEA: Spatially-resolved Transcriptomics via Epitope Anchoring

Use the Adjacency Score to evaluate colocalization of given pairs of genes mapped to the CODEX spatial positions Takes matrices and data frames instead of STvEA.data class

Description

Use the Adjacency Score to evaluate colocalization of given pairs of genes mapped to the CODEX spatial positions Takes matrices and data frames instead of STvEA.data class

Usage

AdjScoreGenes.internal(
  adj_matrix,
  codex_mRNA,
  gene_pairs,
  c = 0,
  num_cores = 1,
  num_perms = 1000,
  perm_estimate = T
)

Arguments

adj_matrix	a (preferrably sparse) binary matrix of adjacency between the cells in the CODEX spatial coordinates
codex_mRNA	a (CODEX cells x genes) matrix of the CITE-seq mRNA expression mapped to the CODEX cells
gene_pairs	a 2 column matrix of gene pairs where each row specifies the names of the genes in a pair
c	constant used to determine width of diffusion, must be 0 <= c
num_cores	integer specifying the number of cores to be used in the computation. By default only one core is used. On Windows, this must be set to 1.
num_perms	number of permutations used to build the null distribution for each feature. By default is set to 1000.
perm_estimate	boolean indicating whether Gaussian distribution parameters should be determined from num_perms permutations to estimate the p-value. By default is set to TRUE.

CamaraLab/STvEA documentation built on April 2, 2024, 6:07 a.m.