muleaData - GMT Datasets for the mulea Package

Eszter Ari

arieszter@gmail.com

Márton Ölbei

Leila Gul

Balázs Bohár

Tamás Stirling

2024-11-05

muleaData is an ExperimentHubData Bioconductor package providing pre-processed gene set 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 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:

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 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 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("ExperimentHub")
BiocManager::install("muleaData")

Example

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


# Calling the ExperimentHub library.
library(ExperimentHub)
#> Loading required package: BiocGenerics
#> 
#> Attaching package: 'BiocGenerics'
#> The following objects are masked from 'package:stats':
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from 'package:base':
#> 
#>     Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#>     as.data.frame, basename, cbind, colnames, dirname, do.call,
#>     duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
#>     lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#>     pmin.int, rank, rbind, rownames, sapply, saveRDS, setdiff, table,
#>     tapply, union, unique, unsplit, which.max, which.min
#> Loading required package: AnnotationHub
#> Loading required package: BiocFileCache
#> Loading required package: dbplyr

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

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

# Checking the muleaData variable.
muleaData
#> ExperimentHub with 879 records
#> # snapshotDate(): 2024-10-24
#> # $dataprovider: muleaData
#> # $species: Drosophila melanogaster, Homo sapiens, Mus musculus, Caenorhabdi...
#> # $rdataclass: data.frame
#> # additional mcols(): taxonomyid, genome, description,
#> #   coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
#> #   rdatapath, sourceurl, sourcetype 
#> # retrieve records with, e.g., 'object[["EH8571"]]' 
#> 
#>            title                                                              
#>   EH8571 | Genomic_location_Ensembl_Arabidopsis_thaliana_10genes_EnsemblID.rds
#>   EH8572 | Genomic_location_Ensembl_Arabidopsis_thaliana_10genes_EntrezID.rds 
#>   EH8573 | Genomic_location_Ensembl_Arabidopsis_thaliana_10genes_GeneSymbol...
#>   EH8574 | Genomic_location_Ensembl_Arabidopsis_thaliana_10genes_UniprotID.rds
#>   EH8575 | Genomic_location_Ensembl_Arabidopsis_thaliana_20genes_EnsemblID.rds
#>   ...      ...                                                                
#>   EH9445 | Genomic_location_Ensembl_Zea_mays_5genes_UniprotID.rds             
#>   EH9446 | Protein_domain_PFAM_Zea_mays_EnsemblID.rds                         
#>   EH9447 | Protein_domain_PFAM_Zea_mays_EntrezID.rds                          
#>   EH9448 | Protein_domain_PFAM_Zea_mays_GeneSymbol.rds                        
#>   EH9449 | Protein_domain_PFAM_Zea_mays_UniprotID.rds

# 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/")
#>                                                                        title
#> EH8727  Transcription_factor_TFLink_Caenorhabditis_elegans_All_EnsemblID.rds
#> EH8728   Transcription_factor_TFLink_Caenorhabditis_elegans_All_EntrezID.rds
#> EH8729 Transcription_factor_TFLink_Caenorhabditis_elegans_All_GeneSymbol.rds
#> EH8730  Transcription_factor_TFLink_Caenorhabditis_elegans_All_UniprotID.rds
#> EH8731   Transcription_factor_TFLink_Caenorhabditis_elegans_LS_EnsemblID.rds
#> EH8732    Transcription_factor_TFLink_Caenorhabditis_elegans_LS_EntrezID.rds
#> EH8733  Transcription_factor_TFLink_Caenorhabditis_elegans_LS_GeneSymbol.rds
#> EH8734   Transcription_factor_TFLink_Caenorhabditis_elegans_LS_UniprotID.rds
#> EH8735   Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EnsemblID.rds
#> EH8736    Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EntrezID.rds
#> EH8737  Transcription_factor_TFLink_Caenorhabditis_elegans_SS_GeneSymbol.rds
#> EH8738   Transcription_factor_TFLink_Caenorhabditis_elegans_SS_UniprotID.rds
#>        dataprovider                species taxonomyid genome
#> EH8727    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8728    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8729    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8730    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8731    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8732    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8733    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8734    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8735    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8736    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8737    muleaData Caenorhabditis elegans       6239   <NA>
#> EH8738    muleaData Caenorhabditis elegans       6239   <NA>
#>                                                                                                                                                                                                                                                                                                                                                                         description
#> EH8727 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.
#> EH8728 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.
#> EH8729 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.
#> EH8730 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.
#> EH8731 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.
#> EH8732 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.
#> EH8733 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.
#> EH8734 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.
#> EH8735 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.
#> EH8736 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.
#> EH8737 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.
#> EH8738 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.
#>        coordinate_1_based                     maintainer rdatadateadded
#> EH8727                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8728                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8729                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8730                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8731                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8732                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8733                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8734                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8735                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8736                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8737                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#> EH8738                  1 Eszter Ari arieszter@gmail.com     2024-02-07
#>        preparerclass         tags rdataclass
#> EH8727     muleaData Arabidop.... data.frame
#> EH8728     muleaData Arabidop.... data.frame
#> EH8729     muleaData Arabidop.... data.frame
#> EH8730     muleaData Arabidop.... data.frame
#> EH8731     muleaData Arabidop.... data.frame
#> EH8732     muleaData Arabidop.... data.frame
#> EH8733     muleaData Arabidop.... data.frame
#> EH8734     muleaData Arabidop.... data.frame
#> EH8735     muleaData Arabidop.... data.frame
#> EH8736     muleaData Arabidop.... data.frame
#> EH8737     muleaData Arabidop.... data.frame
#> EH8738     muleaData Arabidop.... data.frame
#>                                                                              rdatapath
#> EH8727  muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_All_EnsemblID.rds
#> EH8728   muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_All_EntrezID.rds
#> EH8729 muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_All_GeneSymbol.rds
#> EH8730  muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_All_UniprotID.rds
#> EH8731   muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_LS_EnsemblID.rds
#> EH8732    muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_LS_EntrezID.rds
#> EH8733  muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_LS_GeneSymbol.rds
#> EH8734   muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_LS_UniprotID.rds
#> EH8735   muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EnsemblID.rds
#> EH8736    muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_SS_EntrezID.rds
#> EH8737  muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_SS_GeneSymbol.rds
#> EH8738   muleaData/Transcription_factor_TFLink_Caenorhabditis_elegans_SS_UniprotID.rds
#>                  sourceurl sourcetype
#> EH8727 https://tflink.net/   Multiple
#> EH8728 https://tflink.net/   Multiple
#> EH8729 https://tflink.net/   Multiple
#> EH8730 https://tflink.net/   Multiple
#> EH8731 https://tflink.net/   Multiple
#> EH8732 https://tflink.net/   Multiple
#> EH8733 https://tflink.net/   Multiple
#> EH8734 https://tflink.net/   Multiple
#> EH8735 https://tflink.net/   Multiple
#> EH8736 https://tflink.net/   Multiple
#> EH8737 https://tflink.net/   Multiple
#> EH8738 https://tflink.net/   Multiple

# 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"]]
#> see ?muleaData and browseVignettes('muleaData') for documentation
#> loading from cache

Session Info

sessionInfo()
#> R version 4.4.1 (2024-06-14)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.1 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.20-bioc/R/lib/libRblas.so 
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: America/New_York
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] muleaData_1.2.0      ExperimentHub_2.14.0 AnnotationHub_3.14.0
#> [4] BiocFileCache_2.14.0 dbplyr_2.5.0         BiocGenerics_0.52.0 
#> 
#> loaded via a namespace (and not attached):
#>  [1] rappdirs_0.3.3          sass_0.4.9              utf8_1.2.4             
#>  [4] generics_0.1.3          BiocVersion_3.20.0      RSQLite_2.3.7          
#>  [7] digest_0.6.37           magrittr_2.0.3          evaluate_1.0.1         
#> [10] fastmap_1.2.0           blob_1.2.4              jsonlite_1.8.9         
#> [13] AnnotationDbi_1.68.0    GenomeInfoDb_1.42.0     DBI_1.2.3              
#> [16] BiocManager_1.30.25     httr_1.4.7              purrr_1.0.2            
#> [19] fansi_1.0.6             UCSC.utils_1.2.0        Biostrings_2.74.0      
#> [22] jquerylib_0.1.4         cli_3.6.3               crayon_1.5.3           
#> [25] rlang_1.1.4             XVector_0.46.0          Biobase_2.66.0         
#> [28] bit64_4.5.2             withr_3.0.2             cachem_1.1.0           
#> [31] yaml_2.3.10             tools_4.4.1             memoise_2.0.1          
#> [34] dplyr_1.1.4             GenomeInfoDbData_1.2.13 filelock_1.0.3         
#> [37] curl_5.2.3              mime_0.12               vctrs_0.6.5            
#> [40] R6_2.5.1                png_0.1-8               stats4_4.4.1           
#> [43] lifecycle_1.0.4         zlibbioc_1.52.0         KEGGREST_1.46.0        
#> [46] S4Vectors_0.44.0        IRanges_2.40.0          bit_4.5.0              
#> [49] pkgconfig_2.0.3         pillar_1.9.0            bslib_0.8.0            
#> [52] glue_1.8.0              xfun_0.49               tibble_3.2.1           
#> [55] tidyselect_1.2.1        knitr_1.48              htmltools_0.5.8.1      
#> [58] rmarkdown_2.29          compiler_4.4.1

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.