buildGRN-methods: Predict a gene regulatory network.

buildGRNR Documentation

Predict a gene regulatory network.

Description

Predict a gene regulatory network using BioConductor annotations.

Usage

buildGRN(
  object,
  assay.type = "RNA",
  species,
  genes.use = NULL,
  zscore = 5,
  blocksize = 500,
  filename = "GRN.R"
)

## S4 method for signature 'CellRouter'
buildGRN(
  object,
  assay.type = "RNA",
  species = c("Hs", "Mm"),
  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.

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.