spatCellCellcom

spatCellCellcom

Description

Spatial Cell-Cell communication scores based on spatial expression of interacting cells

Usage

spatCellCellcom(
  gobject,
  feat_type = NULL,
  spat_unit = NULL,
  spatial_network_name = "Delaunay_network",
  cluster_column = "cell_types",
  random_iter = 1000,
  feat_set_1,
  feat_set_2,
  gene_set_1 = NULL,
  gene_set_2 = NULL,
  log2FC_addendum = 0.1,
  min_observations = 2,
  detailed = FALSE,
  adjust_method = c("fdr", "bonferroni", "BH", "holm", "hochberg", "hommel", "BY",
    "none"),
  adjust_target = c("feats", "cells"),
  do_parallel = TRUE,
  cores = NA,
  set_seed = TRUE,
  seed_number = 1234,
  verbose = c("a little", "a lot", "none")
)

Arguments

Argument

Description

gobject

giotto object to use

feat_type

feature type

spat_unit

spatial unit

spatial_network_name

spatial network to use for identifying interacting cells

cluster_column

cluster column with cell type information

random_iter

number of iterations

feat_set_1

first specific feature set from feature pairs

feat_set_2

second specific feature set from feature pairs

gene_set_1

deprecated, use feat_set_1

gene_set_2

deprecated, use feat_set_2

log2FC_addendum

addendum to add when calculating log2FC

min_observations

minimum number of interactions needed to be considered

detailed

provide more detailed information (random variance and z-score)

adjust_method

which method to adjust p-values

adjust_target

adjust multiple hypotheses at the cell or feature level

do_parallel

run calculations in parallel with mclapply

cores

number of cores to use if do_parallel = TRUE

set_seed

set a seed for reproducibility

seed_number

seed number

verbose

verbose

Details

Statistical framework to identify if pairs of genes (such as ligand-receptor combinations)

are expressed at higher levels than expected based on a reshuffled null distribution of feature expression values in cells that are spatially in proximity to eachother..

  • LR_comb: Pair of ligand and receptor

  • lig_cell_type: cell type to assess expression level of ligand

  • lig_expr: average expression of ligand in lig_cell_type

  • ligand: ligand name

  • rec_cell_type: cell type to assess expression level of receptor

  • rec_expr: average expression of receptor in rec_cell_type

  • receptor: receptor name

  • LR_expr: combined average ligand and receptor expression

  • lig_nr: total number of cells from lig_cell_type that spatially interact with cells from rec_cell_type

  • rec_nr: total number of cells from rec_cell_type that spatially interact with cells from lig_cell_type

  • rand_expr: average combined ligand and receptor expression from random spatial permutations

  • av_diff: average difference between LR_expr and rand_expr over all random spatial permutations

  • sd_diff: (optional) standard deviation of the difference between LR_expr and rand_expr over all random spatial permutations

  • z_score: (optinal) z-score

  • log2fc: log2 fold-change (LR_expr/rand_expr)

  • pvalue: p-value

  • LR_cell_comb: cell type pair combination

  • p.adj: adjusted p-value

  • PI: significanc score: log2fc * -log10(p.adj)

Value

Cell-Cell communication scores for feature pairs based on spatial interaction