buildGRN2-methods: Predict a gene regulatory network.

In edroaldo/fusca: Framework for Unified Single-Cell Analysis

Predict a gene regulatory network.

Description

Predict a gene regulatory network allowing a customized list of transcription factors or genes (tfs).

Usage

buildGRN2(
  object,
  assay.type = "RNA",
  species = c("Hs", "Mm"),
  tfs = NULL,
  genes.use = NULL,
  zscore = 5,
  blocksize = 500,
  filename = "GRN.R"
)

## S4 method for signature 'CellRouter'
buildGRN2(
  object,
  assay.type = "RNA",
  species = c("Hs", "Mm"),
  tfs = NULL,
  genes.use = NULL,
  zscore = 5,
  blocksize = 500,
  filename = "GRN.R"
)

Arguments

object	CellRouter object.
assay.type	character; the type of data to use.
species	character; species: Hs for Homo Sapiens or Mm for Mus Musculus.
tfs	character vector; transcription factors to use for GRN reconstruction.
genes.use	character vector; genes to include in the gene regulatory network. The default is to use all genes.
zscore	numeric; zscore threshold to identify putative regulatory interactions.
blocksize	numeric; size of the blocks in which genes will be scaled.
filename	character; filename where the GRN data will be saved.

Value

list; the GNR with the gene regulatory network graph, the GRN_table with the gene regulatory network table, and the the tfs with the transcription factors.

edroaldo/fusca documentation built on March 1, 2023, 1:43 p.m.