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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