Last updated: 2025-06-27
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| File | Version | Author | Date | Message |
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| Rmd | dfb1ef2 | Dave Tang | 2025-06-27 | Caenorhabditis elegans |
The biomaRt package provides an interface to BioMart databases provided by Ensembl.
biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite. The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. The most prominent examples of BioMart databases are maintain by Ensembl, which provides biomaRt users direct access to a diverse set of data and enables a wide range of powerful online queries from gene annotation to database mining.
For more information, check out the Accessing Ensembl annotation with biomaRt guide.
To begin, install the {biomaRt} package.
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("biomaRt")Load package.
packageVersion("biomaRt")[1] '2.64.0'suppressPackageStartupMessages(library(biomaRt))Use mirror.
ensembl <- useEnsembl(biomart = "ensembl", mirror = "asia")
ensemblObject of class 'Mart':
Using the ENSEMBL_MART_ENSEMBL BioMart database
No dataset selected.Connect to the selected BioMart database by using
useMart().
avail_datasets <- listDatasets(ensembl)
head(avail_datasets) dataset description
1 abrachyrhynchus_gene_ensembl Pink-footed goose genes (ASM259213v1)
2 acalliptera_gene_ensembl Eastern happy genes (fAstCal1.3)
3 acarolinensis_gene_ensembl Green anole genes (AnoCar2.0v2)
4 acchrysaetos_gene_ensembl Golden eagle genes (bAquChr1.2)
5 acitrinellus_gene_ensembl Midas cichlid genes (Midas_v5)
6 amelanoleuca_gene_ensembl Giant panda genes (ASM200744v2)
version
1 ASM259213v1
2 fAstCal1.3
3 AnoCar2.0v2
4 bAquChr1.2
5 Midas_v5
6 ASM200744v2Look for C. elegans datasets by searching the description column.
idx <- grep(pattern = "elegans", avail_datasets$dataset, ignore.case = TRUE)
avail_datasets[idx, ] dataset description
27 celegans_gene_ensembl Caenorhabditis elegans (Nematode, N2) genes (WBcel235)
version
27 WBcel235Connect to the selected BioMart database and Caenorhabditis elegans dataset.
ensembl <- useEnsembl(biomart = "ensembl", mirror = "asia", dataset=avail_datasets[idx, 'dataset'])
ensemblObject of class 'Mart':
Using the ENSEMBL_MART_ENSEMBL BioMart database
Using the celegans_gene_ensembl datasetBuilding a query, requires three things:
Use listFilters() to show available filters.
avail_filters <- listFilters(ensembl)
head(avail_filters) name
1 chromosome_name
2 start
3 end
4 strand
5 chromosomal_region
6 with_biogrid
description
1 Chromosome/scaffold name
2 Start
3 End
4 Strand
5 e.g. 1:100:10000:-1, 1:100000:200000:1
6 With BioGRID Interaction data, The General Repository for Interaction Datasets ID(s)Use listAttributes() to show available attributes.
avail_attributes <- listAttributes(ensembl)
avail_attributes |>
head() name description page
1 ensembl_gene_id Gene stable ID feature_page
2 ensembl_transcript_id Transcript stable ID feature_page
3 ensembl_peptide_id Protein stable ID feature_page
4 ensembl_exon_id Exon stable ID feature_page
5 description Gene description feature_page
6 chromosome_name Chromosome/scaffold name feature_pageThe getBM() function is the main query function in
{biomaRt}; use it once you have identified your attributes of interest
and filters to use. Note that the gene IDs aren’t really Ensembl Gene
IDs.
gene_ids <- c("WBGene00000007", "WBGene00000027", "WBGene00000056", "WBGene00000071")
getBM(
attributes=c('ensembl_gene_id', 'external_gene_name', 'description'),
filters = 'ensembl_gene_id',
values = gene_ids,
mart = ensembl
) -> res
res ensembl_gene_id external_gene_name
1 WBGene00000007 aat-6
2 WBGene00000027 abu-4
3 WBGene00000056 acr-17
4 WBGene00000071 acy-4
description
1 Amino acid transporter protein 6 [Source:NCBI gene (formerly Entrezgene);Acc:188421]
2 Activated in Blocked Unfolded protein response [Source:NCBI gene (formerly Entrezgene);Acc:353458]
3 AcetylCholine Receptor;Neur_chan_memb domain-containing protein [Source:NCBI gene (formerly Entrezgene);Acc:191603]
4 adenylate cyclase [Source:NCBI gene (formerly Entrezgene);Acc:178949]All gene IDs.
gtf_file <- "https://ftp.ensembl.org/pub/release-113/gtf/caenorhabditis_elegans/Caenorhabditis_elegans.WBcel235.113.gtf.gz"
if(file.exists(basename(gtf_file)) == FALSE){
download.file(url = gtf_file, destfile = basename(gtf_file))
}
gtf_cols <- c(
"seqname",
"source",
"feature",
"start",
"end",
"score",
"strand",
"frame",
"attribute"
)
gtf <- readr::read_tsv(file = gtf_file, comment = "#", col_names = gtf_cols, show_col_types = FALSE)
gtf |>
dplyr::filter(feature == "gene") |>
dplyr::select(attribute) |>
tidyr::separate_rows(attribute, sep = ";\\s*") |>
dplyr::filter(grepl("gene_id", attribute)) |>
tidyr::separate(attribute, c('key', 'value'), sep = "\\s") |>
dplyr::pull(value) |>
gsub(pattern ='"', replacement = "") -> all_gene_ids
length(all_gene_ids) == length(unique(all_gene_ids))[1] TRUEGet gene names and descriptions.
getBM(
attributes=c('ensembl_gene_id', 'external_gene_name', 'description'),
filters = 'ensembl_gene_id',
values = all_gene_ids,
mart = ensembl
) -> all_gene_info
head(all_gene_info) ensembl_gene_id external_gene_name
1 WBGene00000003 aat-2
2 WBGene00000007 aat-6
3 WBGene00000014 abf-3
4 WBGene00000015 abf-4
5 WBGene00000022 abt-4
6 WBGene00000024 abu-1
description
1 Amino Acid Transporter [Source:NCBI gene (formerly Entrezgene);Acc:184126]
2 Amino acid transporter protein 6 [Source:NCBI gene (formerly Entrezgene);Acc:188421]
3 AntiBacterial Factor related [Source:NCBI gene (formerly Entrezgene);Acc:186202]
4 AntiBacterial Factor related [Source:NCBI gene (formerly Entrezgene);Acc:189702]
5 ABC transporter domain-containing protein [Source:NCBI gene (formerly Entrezgene);Acc:178559]
6 Activated in Blocked Unfolded protein response [Source:NCBI gene (formerly Entrezgene);Acc:181800]Save lookup table.
readr::write_csv(x = all_gene_info, file = "data/celegans_gene_info.csv.gz")Find GO attribute names.
grep("^go", avail_attributes$name, ignore.case=TRUE, value=TRUE)[1] "go_id" "go_linkage_type" "goslim_goa_accession"
[4] "goslim_goa_description"Query.
getBM(
attributes=c("ensembl_gene_id", "go_id"),
filters="ensembl_gene_id",
values = all_gene_ids,
mart = ensembl
) -> all_gene_go_ids
head(all_gene_go_ids) ensembl_gene_id go_id
1 WBGene00000003 GO:0016020
2 WBGene00000003 GO:0055085
3 WBGene00000003 GO:0022857
4 WBGene00000003 GO:0003333
5 WBGene00000003 GO:1902475
6 WBGene00000003 GO:0015179Save GO table.
readr::write_csv(x = all_gene_go_ids, file = "data/celegans_gene_id_to_go_id.csv.gz")
sessionInfo()R version 4.5.0 (2025-04-11)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 24.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[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: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] biomaRt_2.64.0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] KEGGREST_1.48.1 xfun_0.52 bslib_0.9.0
[4] httr2_1.1.2 processx_3.8.6 Biobase_2.68.0
[7] tzdb_0.5.0 callr_3.7.6 vctrs_0.6.5
[10] tools_4.5.0 ps_1.9.1 generics_0.1.4
[13] parallel_4.5.0 curl_6.4.0 stats4_4.5.0
[16] tibble_3.3.0 AnnotationDbi_1.70.0 RSQLite_2.4.1
[19] blob_1.2.4 pkgconfig_2.0.3 dbplyr_2.5.0
[22] S4Vectors_0.46.0 lifecycle_1.0.4 GenomeInfoDbData_1.2.14
[25] compiler_4.5.0 stringr_1.5.1 git2r_0.36.2
[28] Biostrings_2.76.0 progress_1.2.3 getPass_0.2-4
[31] httpuv_1.6.16 GenomeInfoDb_1.44.0 htmltools_0.5.8.1
[34] sass_0.4.10 yaml_2.3.10 tidyr_1.3.1
[37] later_1.4.2 pillar_1.10.2 crayon_1.5.3
[40] jquerylib_0.1.4 whisker_0.4.1 cachem_1.1.0
[43] tidyselect_1.2.1 digest_0.6.37 stringi_1.8.7
[46] purrr_1.0.4 dplyr_1.1.4 rprojroot_2.0.4
[49] fastmap_1.2.0 cli_3.6.5 magrittr_2.0.3
[52] readr_2.1.5 withr_3.0.2 filelock_1.0.3
[55] prettyunits_1.2.0 UCSC.utils_1.4.0 promises_1.3.3
[58] rappdirs_0.3.3 bit64_4.6.0-1 rmarkdown_2.29
[61] XVector_0.48.0 httr_1.4.7 bit_4.6.0
[64] png_0.1-8 hms_1.1.3 memoise_2.0.1
[67] evaluate_1.0.4 knitr_1.50 IRanges_2.42.0
[70] BiocFileCache_2.16.0 rlang_1.1.6 Rcpp_1.0.14
[73] glue_1.8.0 DBI_1.2.3 xml2_1.3.8
[76] BiocGenerics_0.54.0 vroom_1.6.5 rstudioapi_0.17.1
[79] jsonlite_2.0.0 R6_2.6.1 fs_1.6.6