cellProximityEnrichment#

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Last Updated: Mar 11, 2023

Description#

Compute cell-cell interaction enrichment (observed vs expected)

Usage#

cellProximityEnrichment(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  spatial_network_name = "Delaunay_network",
  cluster_column,
  number_of_simulations = 1000,
  adjust_method = c("none", "fdr", "bonferroni", "BH", "holm", "hochberg", "hommel",
    "BY"),
  set_seed = TRUE,
  seed_number = 1234
)

Arguments#

gobject

giotto object

spat_unit

spatial unit

feat_type

feature type

spatial_network_name

name of spatial network to use

cluster_column

name of column to use for clusters

number_of_simulations

number of simulations to create expected observations

adjust_method

method to adjust p.values

set_seed

use of seed

seed_number

seed number to use

Details#

Spatial proximity enrichment or depletion between pairs of cell types is calculated by calculating the observed over the expected frequency of cell-cell proximity interactions. The expected frequency is the average frequency calculated from a number of spatial network simulations. Each individual simulation is obtained by reshuffling the cell type labels of each node (cell) in the spatial network.

Value#

List of cell Proximity scores (CPscores) in data.table format. The first data.table (raw_sim_table) shows the raw observations of both the original and simulated networks. The second data.table (enrichm_res) shows the enrichment results.