inst/examples/example_cisTarget.R

# Example for running RcisTarget using cisTarget() function (workflow wrapper)

\dontrun{

##################################################
### Load your gene sets
# As example, the package includes an Hypoxia gene set:
txtFile <- paste(file.path(system.file('examples', package='RcisTarget')),
                 "hypoxiaGeneSet.txt", sep="/")
geneLists <- list(hypoxia=read.table(txtFile, stringsAsFactors=FALSE)[,1])

#### Load databases
## Motif rankings: Select according to organism and distance around TSS
## (See the vignette for URLs to download)
motifRankings <- importRankings("~/databases/hg38_10kbp_up_10kbp_down_full_tx_v10_clust.genes_vs_motifs.rankings.feather")

## Motif - TF annotation:
data("motifAnnotations_hgnc") # human TFs (for motif collection 10)
##################################################

# Run (R)cisTarget
motifEnrichmentTable_wGenes <- cisTarget(geneLists, motifRankings,
  motifAnnot_direct=hg19_direct_motifAnnotation,
  nesThreshold=3.5, geneErnMethod="aprox", nCores=2)

}

# Load results from analysis
load(paste(file.path(system.file('examples', package='RcisTarget')),
           "motifEnrichmentTable_wGenes.RData", sep="/"))


### Exploring the output:
# Note: If using the fake-database, the results are not meaningful

# Number of enriched motifs (Over the given NES threshold)
nrow(motifEnrichmentTable_wGenes)

# Available info (columns)
colnames(motifEnrichmentTable_wGenes)

# The object returned is a data.table (for faster computation),
# which has a diferent syntax from the standard data.frame or matrix
# Feel free to convert it to a data.frame (as.data.frame())
class(motifEnrichmentTable_wGenes)
motifEnrichmentTable_wGenes[,1:5]

# Enriched genes
enrGenes <- as.character(motifEnrichmentTable_wGenes[1,"enrichedGenes"])
strsplit(enrGenes, ";")


# Interactive exploration
motifEnrichmentTable_wGenes <- (motifEnrichmentTable_wGenes)
DT::datatable(motifEnrichmentTable_wGenes[,1:9], escape = FALSE, filter="top",
              options=list(pageLength=5))
# Note: If using the fake database, the results of this analysis are meaningless
aertslab/RcisTarget documentation built on March 7, 2024, 11:21 p.m.