IDPotentialLigands: Identify potential ligands for ligand activity prediction

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

Identify potential ligands for ligand activity prediction

Description

Identify potential ligands for ligand activity prediction

Usage

IDPotentialLigands(
  seu,
  assay = "SCT",
  slot = "data",
  min.pct = 0.025,
  species = "human",
  database = "OmniPath",
  ligands = NULL,
  recepts = NULL
)

Arguments

seu	A Seurat object
assay	Assay in Seurat object from which to pull expression values
slot	Slot within assay from which to pull expression values
min.pct	Minimum percentage of cells in which a gene must be detected in order to be considered an "expressed" gene. Default 0.025 (ie. 2.5%)
species	character. Name of species from which to load ligand-receptor databases. One of: "human", "mouse", "rat". Default: "human"
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.

Value

Returns a list of length 2: 1) a character vector of potential ligands, 2) a character vector of background expressed genes

BlishLab/scriabin documentation built on July 5, 2023, 1:14 a.m.