View source: R/Investigate_Functional_Enrichments.R
listOntologies | R Documentation |
listOntologies()
obtains a character vector
of the available
ontologies for functional enrichment analysis by GREAT for a specified version
and genome build.
listOntologies(
genome = c("hg38", "hg19", "hg18", "mm10", "mm9", "danRer7"),
version = c("4.0.4", "3.0.0", "2.0.2"),
verbose = TRUE
)
genome |
A |
version |
A |
verbose |
A |
listOntologies()
generates the possible ontologies to use for
functional enrichment analysis in enrichModule()
. Supported ontologies may
change over time, so this function queries GREAT using the rGREAT
package to get the ones currently available.
GREAT supports different genomes depending on the version:
hg38
, hg19
, mm10
, mm9
hg19
, mm10
, mm9
, danRer7
hg19
, hg18
, mm9
, danRer7
A character vector
.
getModules()
to build a comethylation network and identify
modules of comethylated regions.
annotateModule()
and getGeneList()
to annotate a set of
regions with genes and regulatory context and then extract
the gene symbols or IDs.
enrichModule()
and plotEnrichment()
to investigate
functional enrichment of module regions with GREAT.
## Not run:
# Get Comethylation Modules
modules <- getModules(methAdj, power = sft$powerEstimate, regions = regions,
corType = "pearson", file = "Modules.rds")
# Annotate Modules
regionsAnno <- annotateModule(regions, module = "bisque4",
genome = "hg38",
file = "Annotated_bisque4_Module_Regions.txt")
geneList_bisque4 <- getGeneList(regionsAnno, module = "bisque4")
# Analyze Functional Enrichment
ontologies <- listOntologies("hg38", version = "4.0.4")
enrich_bisque4 <- enrichModule(regions, module = "bisque4",
genome = "hg38",
file = "bisque4_Module_Enrichment.txt")
plotEnrichment(enrich_bisque4,
file = "bisque4_Module_Enrichment_Plot.pdf")
## End(Not run)
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