enrichR can be installed from Github or soon from CRAN.
websiteLive <- TRUE
library(devtools) install_github("wjawaid/enrichR")
The package can be downloaded from CRAN using:
install.packages("enrichR")
enrichR provides an interface to the Enrichr database [@kuleshov_enrichr:_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) websiteLive <- getOption("enrichR.live") if (websiteLive) { listEnrichrSites() setEnrichrSite("Enrichr") # Human genes }
Then find the list of all available databases from Enrichr.
if (websiteLive) dbs <- listEnrichrDbs()
## if (is.null(dbs)) websiteLive <- FALSE if (websiteLive) head(dbs)
library(knitr) if (websiteLive) kable(head(dbs[c(1:6),-4]))
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) }
Now view the results table.
if (websiteLive) enriched[["GO_Biological_Process_2015"]]
success <- ifelse(exists("enriched"), TRUE, FALSE) & websiteLive success <- success & (length(enriched) >= 3) success <- success & all(dim(enriched[[3]]) > 2) if (success) { x <- head(enriched[["GO_Biological_Process_2015"]]) x[,1] <- gsub("GO:", "GO_", x[,1]) kable(x) }
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") }
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