Retrieve Gene Sets From an Enrichr Library

This function retrieves all gene sets in a given Enrichr library. If a term is supplied, only the gene set associated with that term will be returned.

Usage

rba_enrichr_gene_sets(gene_set_library, term = NULL, organism = "human", ...)

Arguments

gene_set_library: A valid gene-set library name which exists in the results retrieved via rba_enrichr_libs.
term: (optional) An exact Enrichr term name. If left NULL, all gene sets in the supplied library will be returned.
organism: (default = "human") Which model organism version of Enrichr to use? Available options are: "human", (H. sapiens & M. musculus), "fly" (D. melanogaster), "yeast" (S. cerevisiae), "worm" (C. elegans) and "fish" (D. rerio).
...: rbioapi option(s). See rba_options's arguments manual for more information on available options.

Value

A named list of character vectors. Each element name is an Enrichr term and the corresponding character vector contains the genes in that gene set. If the save_file option was set to TRUE or a valid path, the raw GMT file will also be saved to the requested path.

Details

If the available Enrichr library names are not already stored in the "rba_enrichr_libs" global option, this function will retrieve and store them before validating the supplied library name.

Corresponding API Resources

"GET https://maayanlab.cloud/Enrichr/geneSetLibrary"

Saving Gene Sets as a GMT File

To save the raw server's response as a GMT file, supply the save_file rbioapi option through .... Set it to TRUE to automatically generate a proper file path, or supply a character string with a valid file or directory path. See rba_options's arguments manual for more information on available options. The organism will be included in the automatically-generated file name. If a term is supplied, its name will also be included.

References

Chen, E.Y., Tan, C.M., Kou, Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. Bioinformatics 14, 128 (2013). https://doi.org/10.1186/1471-2105-14-128
Maxim V. Kuleshov, Matthew R. Jones, Andrew D. Rouillard, Nicolas F. Fernandez, Qiaonan Duan, Zichen Wang, Simon Koplev, Sherry L. Jenkins, Kathleen M. Jagodnik, Alexander Lachmann, Michael G. McDermott, Caroline D. Monteiro, Gregory W. Gundersen, Avi Ma’ayan, Enrichr: a comprehensive gene set enrichment analysis web server 2016 update, Nucleic Acids Research, Volume 44, Issue W1, 8 July 2016, Pages W90–W97, https://doi.org/10.1093/nar/gkw377
Xie, Z., Bailey, A., Kuleshov, M. V., Clarke, D. J. B., Evangelista, J. E., Jenkins, S. L., Lachmann, A., Wojciechowicz, M. L., Kropiwnicki, E., Jagodnik, K. M., Jeon, M., & Ma’ayan, A. (2021). Gene set knowledge discovery with Enrichr. Current Protocols, 1, e90. doi: 10.1002/cpz1.90
Enrichr API Documentation
Citations note on Enrichr website

Examples

# \donttest{
rba_enrichr_gene_sets(
    gene_set_library = "Reactome_Pathways_2024",
    term = "Signaling by NOTCH")
# }
# \donttest{
rba_enrichr_gene_sets(gene_set_library = "Reactome_Pathways_2024")
# }
if (FALSE) { # \dontrun{
rba_enrichr_gene_sets(
    gene_set_library = "Reactome_Pathways_2024",
    save_file = "Reactome_Pathways_2024.gmt")
} # }