| Title: | Genes Sets for Functional Enrichment Analysis with the 'mulea' R Package |
|---|---|
| Description: | ExperimentHubData package for the 'mulea' comprehensive overrepresentation and functional enrichment analyser R package. Here we provide ontologies (gene sets) in a data.frame for 27 different organisms, ranging from Escherichia coli to human, all acquired from publicly available data sources. Each ontology is provided with multiple gene and protein identifiers. Please see the NEWS file for a list of changes in each version. |
| Authors: | Eszter Ari [aut, cre] (ORCID: <https://orcid.org/0000-0001-7774-1067>), Márton Ölbei [aut] (ORCID: <https://orcid.org/0000-0002-4903-6237>), Lejla Gul [aut], Balázs Bohár [aut] (ORCID: <https://orcid.org/0000-0002-3033-5448>), Tamás Stirling [aut] (ORCID: <https://orcid.org/0000-0002-8964-6443>) |
| Maintainer: | Eszter Ari <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 1.8.0 |
| Built: | 2026-10-10 11:16:28 UTC |
| Source: | https://github.com/bioc/muleaData |
muleaData provides pre-processed gene set (ontology) data for
use with the mulea R package, a comprehensive tool
for overrepresentation and functional enrichment analysis.
mulea leverages ontologies (gene and protein sets) stored
in the standardized Gene Matrix Transposed (GMT) format.
We provide these GMT files for 27 different model organisms, ranging from
Escherichia coli to human.
These files are compiled from publicly available sources and include various
gene and protein identifiers like 'UniProt' protein IDs,
'Entrez', 'Gene Symbol', and 'Ensembl' gene IDs.
The GMT files and the scripts we applied to create them are available at
the 'ELTEbioinformatics/GMT_files_for_mulea' github repository.
For the muleaData we read these GMT files with the
mulea::read_gmt() function and saved them to
.rds files with the standard R saveRDS() function.
query(ExperimentHub::ExperimentHub(), "muleaData")query(ExperimentHub::ExperimentHub(), "muleaData")
An 'ExperimentHub' object data frame with 879 records
containing gene sets (ontologies) from 27 species,
collected from 16 data sources.
Each record contains a data.frame created from a gene set
stored in Gene Matrix Transposed (GMT) format,
read by the mulea::read_gmt() command.
These data.frame GMT objects contains 3 columns:
'ontology_id': Ontology identifier that uniquely identifies the element within the referenced ontology.
'ontology_name': Ontology name or description that provides a user-friendly label or textual description for the 'ontology_id'.
'list_of_values': Associated genes or proteins that is a vector of identifiers of genes or proteins belonging to the 'ontology_id'.
The muleaData object is generated dynamically by querying the
ExperimentHub package.
The data were downloaded from these sources and formatted to GMT files:
http://atrm.gao-lab.org/
http://flyatlas.org/atlas.cgi
http://geneontology.org/
http://signalink.org/
http://www.yeastract.com
https://github.com/saezlab/dorothea
https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2022/php/index.php
https://reactome.org/
https://regulondb.ccg.unam.mx/
https://tflink.net/
https://wiki.flybase.org/wiki/FlyBase:ModENCODE_data_at_FlyBase
https://www.ebi.ac.uk/interpro/
https://www.ensembl.org
https://www.grnpedia.org/trrust/
https://www.pathwaycommons.org/
https://www.wikipathways.org
# Calling the ExperimentHub library. library(ExperimentHub) # Downloading the metadata from ExperimentHub. eh <- ExperimentHub() # Creating the muleaData variable. muleaData <- query(ExperimentHub::ExperimentHub(), "muleaData") # Checking the muleaData variable. muleaData # Calling dplyr library to explore the data library(dplyr) # Looking for the ExperimentalHub ID of i.e. target genes of transcription # factors from TFLink in Caenorhabditis elegans. mcols(muleaData) %>% as.data.frame() %>% dplyr::filter(species == "Caenorhabditis elegans" & sourceurl == "https://tflink.net/") # Creating a variable for the GMT data.frame of EH8735. # EH8735 contains small-scale measurement results, where the target genes are # coded with Ensembl ID-s Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EnsemblID <- muleaData[["EH8735"]]# Calling the ExperimentHub library. library(ExperimentHub) # Downloading the metadata from ExperimentHub. eh <- ExperimentHub() # Creating the muleaData variable. muleaData <- query(ExperimentHub::ExperimentHub(), "muleaData") # Checking the muleaData variable. muleaData # Calling dplyr library to explore the data library(dplyr) # Looking for the ExperimentalHub ID of i.e. target genes of transcription # factors from TFLink in Caenorhabditis elegans. mcols(muleaData) %>% as.data.frame() %>% dplyr::filter(species == "Caenorhabditis elegans" & sourceurl == "https://tflink.net/") # Creating a variable for the GMT data.frame of EH8735. # EH8735 contains small-scale measurement results, where the target genes are # coded with Ensembl ID-s Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EnsemblID <- muleaData[["EH8735"]]