GitHub - jokergoo/rGREAT: GREAT Analysis - Functional Enrichment on Genomic Regions (original) (raw)

GREAT Analysis - Functional Enrichment on Genomic Regions

GREAT (Genomic Regions Enrichment of Annotations Tool) is a type of functional enrichment analysis directly performed on genomic regions. This package implements the GREAT algorithm (the local GREAT analysis), also it supports directly interacting with the GREAT web service (the online GREAT analysis). Both analysis can be viewed by a Shiny application.

Install

rGREAT is available on Bioconductor (http://bioconductor.org/packages/devel/bioc/html/rGREAT.html)

if(!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("rGREAT")

If you want the latest version, install it directly from GitHub:

library(devtools) install_github("jokergoo/rGREAT")

Citation

Zuguang Gu, et al., rGREAT: an R/Bioconductor package for functional enrichment on genomic regions. Bioinformatics, https://doi.org/10.1093/bioinformatics/btac745

Online GREAT analysis

With online GREAT analysis, the input regions will be directly submitted to GREAT server, and the results are automatically retrieved from GREAT server.

set.seed(123) gr = randomRegions(nr = 1000, genome = "hg19")

job = submitGreatJob(gr) tbl = getEnrichmentTables(job)

Local GREAT analysis

rGREAT also implements the GREAT algorithms locally and it can be seamlessly integrated to the Bioconductor annotation ecosystem. This means, theoretically, with rGREAT, it is possible to perform GREAT analysis with any organism and with any type of gene set collection / ontology

res = great(gr, "MSigDB:H", "TxDb.Hsapiens.UCSC.hg19.knownGene") tb = getEnrichmentTable(res)

To apply great() on other organisms, set the biomart_dataset argument:

giant panda

great(gr, "GO:BP", biomart_dataset = "amelanoleuca_gene_ensembl")

License

MIT @ Zuguang Gu