Calculate Spatial Cell-Cell Communication Scores¶
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spatCellCellcom()
Spatial Cell-Cell communication scores based on spatial expression of interacting cells.
spatCellCellcom(
gobject,
spatial_network_name = "Delaunay_network",
cluster_column = "cell_types",
random_iter = 1000,
gene_set_1,
gene_set_2,
log2FC_addendum = 0.1,
min_observations = 2,
detailed = FALSE,
adjust_method = c("fdr", "bonferroni", "BH", "holm", "hochberg", "hommel", "BY",
"none"),
adjust_target = c("genes", "cells"),
do_parallel = TRUE,
cores = NA,
set_seed = TRUE,
seed_number = 1234,
verbose = c("a little", "a lot", "none")
)
Arguments¶
gobject |
giotto object to use |
spatial_network_name |
spatial network to use for identifying interacting cells |
cluster_column |
cluster column with cell type information |
random_iter |
number of iterations |
gene_set_1 |
first specific gene set from gene pairs |
gene_set_2 |
second specific gene set from gene pairs |
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 gene 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 |
Value¶
A cell-Cell communication score for gene pairs based on expression only.
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 gene expression values in cells that are spatially in proximity to each other.
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: significance score: log2fc * -log10(p.adj)