BuildWeightedInteraction: Build summarized interaction graph weighted by predicted...

In BlishLab/scriabin: Single-cell resolved interaction analysis through binning

Build summarized interaction graph weighted by predicted ligand activities

Description

Build summarized interaction graph weighted by predicted ligand activities

Usage

BuildWeightedInteraction(
  object,
  nichenet_results,
  assay = "SCT",
  slot = "data",
  pearson.cutoff = 0.075,
  scale.factors = c(1.5, 3),
  species = "human",
  database = "OmniPath",
  ligands = NULL,
  recepts = NULL,
  correct.depth = T,
  graph_name = "weighted_interaction"
)

Arguments

object	A Seurat object
nichenet_results	List or matrix. Predicted ligand activities using Scriabin's implementation of NicheNet in RankActiveLigands
assay	Assay in Seurat object from which to pull expression values
slot	Slot within assay from which to pull expression values
pearson.cutoff	numeric. Threshold for determining which ligand activities are "active". Ligands below this threshold will be considered inactive and not used for weighting. Default: 0.075
scale.factors	numeric. Determines the magnitude of ligand and receptor expression values weighting by their predicted activities. Given scale factors of c(x,y), ligand-receptor pairs where the ligand's pearson = pearson.cutoff will be weighted by a factor of x, and the ligand with the highest pearson will be weighted by a factor of y. Default: c(1.5,3).
species	Name of species for which to pull ligand-receptor interactions. One of "human", "mouse", or "rat"
database	Name of ligand-receptor database to use. Default: "OmniPath" When species is "human", one of: OmniPath, CellChatDB, CellPhoneDB, Ramilowski2015, Baccin2019, LRdb, Kirouac2010, ICELLNET, iTALK, EMBRACE, HPMR, Guide2Pharma, connectomeDB2020, talklr, CellTalkDB When species is "mouse" or "rat", only "OmniPath" is supported. To pass a custom ligand-receptor database to this function, set database = "custom"
ligands	Character vector of custom ligands to use for interaction graph generation. Ignored unless database = "custom" When ligands is supplied, recepts must also be supplied and equidimensional.
recepts	Character vector of custom receptors to use for interaction graph generation. Ignored unless database = "custom" When recepts is supplied, ligands must also be supplied and equidimensional.
correct.depth	Correct summarized interaction graph for sequencing depth by linear regression. The sequencing depth of a cell-cell pair is the sum of UMI counts for each cell
graph_name	Name of summarized interaction graph to place into output. Default "weighted_interaction"
ranked_genes	Cell-resolved gene signatures, used only when specific = T

Value

Returns a Seurat object with a weighted summarized interaction graph in the Graphs slot

References

Browaeys, et al. Nature Methods (2019)

BlishLab/scriabin documentation built on Sept. 16, 2024, 1:19 a.m.