---
title: "muleaData - GMT Datasets for the mulea Package"
author:
- name: "Eszter Ari"
email: "arieszter@gmail.com"
- name: "Márton Ölbei"
- name: "Leila Gul"
- name: "Balázs Bohár"
- name: "Tamás Stirling"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{muleaData}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
```
`muleaData` is an ExperimentHubData Bioconductor package providing
pre-processed gene set data for use with the
[`mulea`](https://github.com/ELTEbioinformatics/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
[GMT_files_for_mulea](https://github.com/ELTEbioinformatics/GMT_files_for_mulea)
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.
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 tuberculosis*
- *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](http://www.flyatlas.org/) | 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](http://data.modencode.org/) | 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](https://mirtarbase.cuhk.edu.cn/~miRTarBase/miRTarBase_2022/php/index.php) | 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](https://geneontology.org/) | 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](https://www.pathwaycommons.org/) | 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](https://reactome.org/) | Collection of biological pathway and interaction data. | Jassal,B. *et al.* (2020) The reactome pathway knowledgebase. *Nucleic Acids Res*, **48**, D498–D503. |
| | [Signalink](http://signalink.org/) | 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](https://www.wikipathways.org/) | Collection of biological pathway and interaction data. | Martens,M. *et al.* (2021) WikiPathways: connecting communities. *Nucleic Acids Res*, **49**, D613–D621. |
| **Protein domain** | [PFAM](http://pfam.xfam.org/) | 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](http://atrm.gao-lab.org/) | 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](https://saezlab.github.io/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](https://regulondb.ccg.unam.mx/) | Transcription factor - target gene interactions for *Escherichia coli* bacteria. | TierrafrÃa,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](https://tflink.net/) | Small- and large-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](https://www.grnpedia.org/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](http://www.yeastract.com/) | 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](https://cran.r-project.org/sources.html). Then install
the developmental version of [Bioconductor](http://bioconductor.org/)
and the `ExperimentHub` library using the following code:
```{r 'install', eval=FALSE}
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ExperimentHub")
BiocManager::install("muleaData")
```
## Example
This is a basic example which shows you how to use the `muleaData`:
```{r 'example'}
# 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. 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"]]
```
# Session Info
```{r 'session_info'}
sessionInfo()
```
# Citation
To cite package `muleaData` in publications use:
C. Turek, M. Olbei, T. Stirling, G. Fekete, E. Tasnadi, L. Gul, B. Bohar,
B. Papp, W. Jurkowski, E. Ari:
mulea - an R package for enrichment analysis using multiple ontologies and
empirical FDR correction. *bioRxiv* (2024),
[doi:10.1101/2024.02.28.582444](https://doi.org/10.1101/2024.02.28.582444).