runSCENIC_2_createRegulons: runSCENIC_2_createRegulons

In aertslab/SCENIC: SCENIC (Single Cell rEgulatory Network Inference and Clustering)

runSCENIC_2_createRegulons

Description

Step 2: RcisTarget (prune co-expression modules using TF-motif enrichment analysis)

Usage

runSCENIC_2_createRegulons(
  scenicOptions,
  minGenes = 20,
  coexMethods = NULL,
  minJakkardInd = 0.8,
  signifGenesMethod = "aprox",
  onlyPositiveCorr = TRUE,
  onlyBestGsPerMotif = TRUE,
  dbIndexCol = "features"
)

Arguments

scenicOptions	Fields used: TODO
minGenes	Minimum size of co-expression gene set (default: 20 genes)
coexMethods	Allows to select the method(s) used to generate the co-expression modules
minJakkardInd	Merge overlapping modules (with Jakkard index >=minJakkardInd; reduces running time).
signifGenesMethod	Method for 'addSignificantGenes'
onlyPositiveCorr	Whether to include only positive-correlated targets in the regulons (default: TRUE).
dbIndexCol	Column containing the feature name in the database (default: 'features')

Details

See the detailed vignette explaining the internal steps.

Value

The output is written in the folders 'int' and 'ouput'

Examples

scenicOptions <- readRDS("int/scenicOptions.Rds")
# In case any settings need to be modified:
scenicOptions@settings$nCores <- 20
scenicOptions@inputDatasetInfo$org <- "mgi" 

runSCENIC_2_createRegulons(scenicOptions)

aertslab/SCENIC documentation built on April 7, 2024, 10 a.m.