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An R interface to the Enrichr database

Wajid Jawaid

2023-04-12

Installation

enrichR can be installed from Github or soon from CRAN.

Github

library(devtools)
install_github("wjawaid/enrichR")

CRAN

The package can be downloaded from CRAN using:

install.packages("enrichR")

Usage example

enrichR provides an interface to the Enrichr database (Kuleshov et al. 2016) hosted at https://maayanlab.cloud/Enrichr/.

By default human genes are selected otherwise select your organism of choice. (This functionality was contributed by Alexander Blume)

library(enrichR)
## Welcome to enrichR
## Checking connection ...
## Enrichr ... Connection is Live!
## FlyEnrichr ... Connection is Live!
## WormEnrichr ... Connection is Live!
## YeastEnrichr ... Connection is Live!
## FishEnrichr ... Connection is Live!
## OxEnrichr ... Connection is Live!
websiteLive <- getOption("enrichR.live")
if (websiteLive) {
    listEnrichrSites()
    setEnrichrSite("Enrichr") # Human genes   
}
## Enrichr ... Connection is Live!
## FlyEnrichr ... Connection is Live!
## WormEnrichr ... Connection is Live!
## YeastEnrichr ... Connection is Live!
## FishEnrichr ... Connection is Live!
## OxEnrichr ... Connection is Live!
## Connection changed to https://maayanlab.cloud/Enrichr/
## Connection is Live!

Then find the list of all available databases from Enrichr.

if (websiteLive) dbs <- listEnrichrDbs()
## if (is.null(dbs)) websiteLive <- FALSE
if (websiteLive) head(dbs)
##   geneCoverage genesPerTerm                      libraryName
## 1        13362          275              Genome_Browser_PWMs
## 2        27884         1284         TRANSFAC_and_JASPAR_PWMs
## 3         6002           77        Transcription_Factor_PPIs
## 4        47172         1370                        ChEA_2013
## 5        47107          509 Drug_Perturbations_from_GEO_2014
## 6        21493         3713          ENCODE_TF_ChIP-seq_2014
##                                                       link numTerms
## 1 http://hgdownload.cse.ucsc.edu/goldenPath/hg18/database/      615
## 2                 http://jaspar.genereg.net/html/DOWNLOAD/      326
## 3                                                               290
## 4           http://amp.pharm.mssm.edu/lib/cheadownload.jsp      353
## 5                         http://www.ncbi.nlm.nih.gov/geo/      701
## 6             http://genome.ucsc.edu/ENCODE/downloads.html      498
##                                    appyter categoryId
## 1 ea115789fcbf12797fd692cec6df0ab4dbc79c6a          1
## 2 7d42eb43a64a4e3b20d721fc7148f685b53b6b30          1
## 3 849f222220618e2599d925b6b51868cf1dab3763          1
## 4 7ebe772afb55b63b41b79dd8d06ea0fdd9fa2630          7
## 5 ad270a6876534b7cb063e004289dcd4d3164f342          7
## 6 497787ebc418d308045efb63b8586f10c526af51          7
geneCoverage genesPerTerm libraryName numTerms appyter categoryId
13362 275 Genome_Browser_PWMs 615 ea115789fcbf12797fd692cec6df0ab4dbc79c6a 1
27884 1284 TRANSFAC_and_JASPAR_PWMs 326 7d42eb43a64a4e3b20d721fc7148f685b53b6b30 1
6002 77 Transcription_Factor_PPIs 290 849f222220618e2599d925b6b51868cf1dab3763 1
47172 1370 ChEA_2013 353 7ebe772afb55b63b41b79dd8d06ea0fdd9fa2630 7
47107 509 Drug_Perturbations_from_GEO_2014 701 ad270a6876534b7cb063e004289dcd4d3164f342 7
21493 3713 ENCODE_TF_ChIP-seq_2014 498 497787ebc418d308045efb63b8586f10c526af51 7

View and select your favourite databases. Then query enrichr, in this case I have used genes associated with embryonic haematopoiesis.

dbs <- c("GO_Molecular_Function_2015", "GO_Cellular_Component_2015", "GO_Biological_Process_2015")
if (websiteLive) {
    enriched <- enrichr(c("Runx1", "Gfi1", "Gfi1b", "Spi1", "Gata1", "Kdr"), dbs)
}
## Uploading data to Enrichr... Done.
##   Querying GO_Molecular_Function_2015... Done.
##   Querying GO_Cellular_Component_2015... Done.
##   Querying GO_Biological_Process_2015... Done.
## Parsing results... Done.

Now view the results table.

if (websiteLive) enriched[["GO_Biological_Process_2015"]]
Term Overlap P.value Adjusted.P.value Old.P.value Old.Adjusted.P.value Odds.Ratio Combined.Score Genes
embryonic hemopoiesis (GO_0035162) 3/24 0.0e+00 0.0000083 0 0 951.0952 16465.833 KDR;GATA1;RUNX1
regulation of myeloid cell differentiation (GO_0045637) 4/156 1.0e-07 0.0000083 0 0 261.0789 4374.968 GFI1B;SPI1;GATA1;RUNX1
regulation of erythrocyte differentiation (GO_0045646) 3/36 1.0e-07 0.0000112 0 0 604.8788 9710.235 GFI1B;SPI1;GATA1
positive regulation of myeloid cell differentiation (GO_0045639) 3/74 1.0e-06 0.0000762 0 0 280.6056 3886.803 GFI1B;GATA1;RUNX1
hemopoiesis (GO_0030097) 3/95 2.1e-06 0.0001299 0 0 216.3261 2832.846 KDR;GATA1;RUNX1
hematopoietic progenitor cell differentiation (GO_0002244) 3/106 2.9e-06 0.0001507 0 0 193.1165 2465.031 SPI1;GATA1;RUNX1

Plot Enrichr GO-BP output. (Plotting function contributed by I-Hsuan Lin)

if (websiteLive) {
    plotEnrich(enriched[[3]], showTerms = 20, numChar = 40, y = "Count", orderBy = "P.value")
}

References

Kuleshov, Maxim V., Matthew R. Jones, Andrew D. Rouillard, Nicolas F. Fernandez, Qiaonan Duan, Zichen Wang, Simon Koplev, et al. 2016. “Enrichr: A Comprehensive Gene Set Enrichment Analysis Web Server 2016 Update.” Nucleic Acids Res 44 (Web Server issue): W90–97.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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