stitam/muleadata

muleaData is an ExperimentHubData Bioconductor package for the mulea R package

muleaData

muleaData is an ExperimentHubData Bioconductor package for the mulea R package. mulea is a comprehensive overrepresentation and functional enrichment analyser R package which reads ontologies (gene and protein sets) in a standardised GMT (Gene Matrix Transposed) format. We provide these GMT files for 27 different model organisms, ranging from Escherichia coli to human, all acquired from publicly available data sources. The GMT files are provided with multiple gene and protein identifiers such as 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 GMT_files_for_mulea repository. For the muleaData we read these GMT files with the mulea::read_gmt() function and saved it to .rds files with the standard R saveRDS() function.

List of species muleaData covers:

• Arabidopsis thaliana
• Bacillus subtilis
• Bacteroides thetaiotaomicron VPI-5482
• Bifidobacterium longum
• Bos taurus
• Caenorhabditis elegans
• Chlamydomonas reinhardtii
• Danio rerio
• Daphnia pulex
• Dictyostelium discoideum
• Drosophila melanogaster
• Drosophila simulans
• Escherichia coli
• Gallus gallus
• Homo sapiens
• Macaca mulatta
• Mus musculus
• Mycobacterium tubercolosis
• Neurospora crassa
• Pan troglodytes
• Rattus norvegicus
• Saccharomyces cerevisiae
• Salmonella enterica subsp. enterica serovar Typhimurium str. LT2
• Schizosaccharomyces pombe
• Tetrahymena thermophila
• Xenopus tropicalis
• Zea mays

Type, name, link and citation of the databases muleaData covers:

Ontology category	Ontology name	Short description of content	Reference
Gene expression	FlyAtlas	Tissue specific expression data for Drosophila melanogaster.	Chintapalli,V.R. et al. (2007) Using FlyAtlas to identify better Drosophila melanogaster models of human disease. Nat Genet, 39, 715–720.
	ModEncode	Functional characterization (cell line, temporal expression, tissue expression, treatment) of elements for Caenorhabditis elegans and Drosophila melanogaster.	The Modencode Consortium et al. (2010) Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science, 330, 1787–1797.
Genomic location	Chromosomal Bands	Location of genes on the chromosome.	Martin,F.J. et al. (2023) Ensembl 2023. Nucleic Acids Res, 51, D933–D941.
	Consecutive genes	n consecutive genes on the chromosome.
miRNA regulation	miRTarBase	Experimentally validated miRNA - target interactions.	Huang,H.-Y. et al. (2022) miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions. Nucleic Acids Res, 50, D222–D230.
Gene Ontology	GO	Gene Ontology (GO) categorizes genes into unified categories and attributes.	The Gene Ontology Consortium et al. (2023) The Gene Ontology knowledgebase in 2023. Genetics, 224, iyad031.
Pathway	Pathway Commons	Collection of biological pathway and interaction data.	Rodchenkov,I. et al. (2020) Pathway Commons 2019 Update: integration, analysis and exploration of pathway data. Nucleic Acids Res, 48, D489–D497.
	Reactome	Collection of biological pathway and interaction data.	Jassal,B. et al. (2020) The reactome pathway knowledgebase. Nucleic Acids Res, 48, D498–D503.
	Signalink	Interaction database focussing on pathways and interactions of pathways.	Csabai,L. et al. (2022) SignaLink3: a multi-layered resource to uncover tissue-specific signaling networks. Nucleic Acids Res, 50, D701–D709.
	Wikipathways	Collection of biological pathway and interaction data.	Martens,M. et al. (2021) WikiPathways: connecting communities. Nucleic Acids Res, 49, D613–D621.
Protein domain	PFAM	Protein domain structure database.	Mistry,J. et al. (2021) Pfam: The protein families database in 2021. Nucleic Acids Res, 49, D412–D419.
Transcription factor regulation	ATRM	Transcription factor - target gene interactions for Arabidopsis thaliana.	Jin,J. et al. (2015) An Arabidopsis transcriptional regulatory map reveals distinct functional and evolutionary features of novel transcription factors. Mol Biol Evol, 32, 1767–1773.
	dorothEA	Transcription factor - target gene interactions for human and mouse.	Garcia-Alonso,L. et al. (2019) Benchmark and integration of resources for the estimation of human transcription factor activities. Genome Res, 29, 1363–1375.
	RegulonDB	Transcription factor - target gene interactions for Escherichia coli bacteria.	Tierrafría,V.H. et al. (2022) RegulonDB 11.0: Comprehensive high-throughput datasets on transcriptional regulation in Escherichia coli K-12. Microb Genom, 8, 000833.
	TFLink	Small- and lagre-scale transcription factor - target gene interactions for human and 6 model organisms.	Liska,O. et al. (2022) TFLink: an integrated gateway to access transcription factor–target gene interactions for multiple species. Database, 2022, baac083.
	TRRUST	Transcription factor - target gene interactions for human.	Han,H. et al. (2018) TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res, 46, D380–D386.
	Yeastract	Transcription factor - target gene interactions for Saccharomyces cerevisiae.	Teixeira,M.C. et al. (2018) YEASTRACT: an upgraded database for the analysis of transcription regulatory networks in Saccharomyces cerevisiae. Nucleic Acids Res, 46, D348–D353.

Installation instructions

Install the developmental version of R from CRAN. Then install the developmental version of Bioconductor and the ExperimentHub library using the following code:

if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
BiocManager::install(version = "3.19")

BiocManager::install("ExperimentHub")

Example

This is a basic example which shows you how to use the muleaData:

# Calling the ExperimentHub library.
library(ExperimentHub)

# Downloading the metadata from ExperimentHub.
eh <- ExperimentHub()

# Creating the muleaData variable.
muleaData <- query(eh, "muleaData")

# Checking the muleaData variable.
muleaData

# Looking for the ExperimentalHub ID of i.e. tagret 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"]]

Citation

To cite package muleaData in publications use:

Ari E, Ölbei M, Gul L, Bohár B (2024). muleaData: ExperimentalData Bioconductor Package for the mulea R Package, Contains Genes Sets for Functional Enrichment Analysis in GMT File Format. R package version 0.99.0, https://github.com/ELTEbioinformatics/muleaData.

Code of Conduct

Please note that the muleaData project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Development tools

• Continuous code testing is possible thanks to GitHub actions through usethis, remotes, and rcmdcheck customized to use Bioconductor’s docker containers and BiocCheck.
• Code coverage assessment is possible thanks to codecov and covr.
• The documentation website is automatically updated thanks to pkgdown.
• The code is styled automatically thanks to styler.
• The documentation is formatted thanks to devtools and roxygen2.

For more details, check the dev directory.

This package was developed using biocthis.