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")
)
Argument | Description |
---|---|
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 |
- 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 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)
Cell-Cell communication scores for gene pairs based on spatial interaction