This package is born out of my own frustration to automate the genomic data retrieval process to create computationally reproducible scripts for large-scale genomics studies. Since I couldn’t find easy-to-use and fully reproducible software libraries I sat down and tried to implement a framework that would enable anyone to automate and standardize the genomic data retrieval process. I hope that this package is useful to others as well and that it helps to promote reproducible research in genomics studies.
I happily welcome anyone who wishes to contribute to this project :) Just drop me an email.
Please find a detailed documentation here.
Please cite biomartr if it was helpful for your research. This will allow me to continue maintaining this project in the future.
Drost HG, Paszkowski J. Biomartr: genomic data retrieval with R. Bioinformatics (2017) 33(8): 1216-1217. doi:10.1093/bioinformatics/btw821.
The vastly growing number of sequenced genomes allows us to perform a new type of biological research. Using a comparative approach these genomes provide us with new insights on how biological information is encoded on the molecular level and how this information changes over evolutionary time.
The first step, however, of any genome based study is to retrieve genomes and their annotation from databases. To automate the retrieval process of this information on a meta-genomic scale, the biomartr package provides interface functions for genomic sequence retrieval and functional annotation retrieval. The major aim of biomartr is to facilitate computational reproducibility and large-scale handling of genomic data for (meta-)genomic analyses. In addition, biomartr aims to address the genome version crisis. With biomartr users can now control and be informed about the genome versions they retrieve automatically. Many large scale genomics studies lack this information and thus, reproducibility and data interpretation become nearly impossible when documentation of genome version information gets neglected.
In detail, biomartr automates genome, proteome, CDS, RNA, Repeats, GFF/GTF (annotation), genome assembly quality, and metagenome project data retrieval from the major biological databases such as
ENSEMBL and ENSEMBLGENOMES were joined - see details here)Furthermore, an interface to the Ensembl Biomart database allows users to retrieve functional annotation for genomic loci using a novel and organism centric search strategy. In addition, users can download entire databases such as
NCBI RefSeqNCBI nrNCBI ntNCBI GenbankENSEMBLwith only one command.
The main difference between the BiomaRt package and the biomartr package is that biomartr extends the functional annotation retrieval procedure of BiomaRt and in addition provides useful retrieval functions for genomes, proteomes, coding sequences, gff files, RNA sequences, Repeat Masker annotations files, and functions for the retrieval of entire databases such as NCBI nr etc.
Please consult the Tutorials section for more details.
In the context of functional annotation retrieval the biomartr package allows users to screen available marts using only the scientific name of an organism of interest instead of first searching for marts and datasets which support a particular organism of interest (which is required when using the BiomaRt package). Furthermore, biomartr allows you to search for particular topics when searching for attributes and filters. I am aware that the similar naming of the packages is unfortunate, but it arose due to historical reasons (please find a detailed explanation here: https://github.com/ropensci/biomartr/blob/master/FAQs.md and here #11).
I also dedicated an entire vignette to compare the BiomaRt and biomartr package functionality in the context of Functional Annotation (where their functionality overlaps which comprises about only 20% of the overall functionality of the biomartr package).
I truly value your opinion and improvement suggestions. Hence, I would be extremely grateful if you could take this 1 minute and 3 question survey (https://goo.gl/forms/Qaoxxjb1EnNSLpM02) so that I can learn how to improve
biomartrin the best possible way. Many many thanks in advance.
The biomartr package relies on some Bioconductor tools and thus requires installation of the following packages:
# Install core Bioconductor packages
if (!requireNamespace("BiocManager"))
install.packages("BiocManager")
BiocManager::install()
# Install package dependencies
BiocManager::install("Biostrings")
BiocManager::install("biomaRt")Now users can install biomartr from CRAN:
With an activated Bioconda channel (see 2. Set up channels), install with:
conda install r-biomartrand update with:
conda update r-biomartror use the docker container:
docker pull quay.io/biocontainers/r-biomartr:<tag>(check r-biomartr/tags for valid values for
The automated retrieval of collections (= Genome, Proteome, CDS, RNA, GFF, Repeat Masker, AssemblyStats files) will make sure that the genome file of an organism will match the CDS, proteome, RNA, GFF, etc file and was generated using the same genome assembly version. One aspect of why genomics studies fail in computational and biological reproducibility is that it is not clear whether CDS, proteome, RNA, GFF, etc files used in a proposed analysis were generated using the same genome assembly file denoting the same genome assembly version. To avoid this seemingly trivial mistake we encourage users to retrieve genome file collections using the biomartr function getCollection() and attach the corresponding output as Supplementary Data to the respective genomics study to ensure computational and biological reproducibility.
# download collection for Saccharomyces cerevisiae
biomartr::getCollection( db = "refseq", organism = "Saccharomyces cerevisiae")Internally, the getCollection() function will now generate a folder named refseq/Collection/Saccharomyces_cerevisiae and will store all genome and annotation files for Saccharomyces cerevisiae in the same folder. In addition, the exact genoem and annotation version will be logged in the doc folder.
Internally, a text file named doc_Saccharomyces_cerevisiae_db_refseq.txt is generated. The information stored in this log file is structured as follows:
File Name: Saccharomyces_cerevisiae_assembly_stats_refseq.txt
Organism Name: Saccharomyces_cerevisiae
Database: NCBI refseq
URL: ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/146/045/GCF_000146045.2_R64/GCF_000146045.2_R64_assembly_stats.txt
Download_Date: Wed Jun 27 15:21:51 2018
refseq_category: reference genome
assembly_accession: GCF_000146045.2
bioproject: PRJNA128
biosample: NA
taxid: 559292
infraspecific_name: strain=S288C
version_status: latest
release_type: Major
genome_rep: Full
seq_rel_date: 2014-12-17
submitter: Saccharomyces Genome DatabaseIn an ideal world this reference file could then be included as supplementary information in any life science publication that relies on genomic information so that reproducibility of experiments and analyses becomes achievable.
Download all mammalian vertebrate genomes from NCBI RefSeq via:
# download all vertebrate genomes
meta.retrieval(kingdom = "vertebrate_mammalian", db = "refseq", type = "genome")All geneomes are stored in the folder named according to the kingdom. In this case vertebrate_mammalian. Alternatively, users can specify the out.folder argument to define a custom output folder path.
Please find all FAQs here.
I would be very happy to learn more about potential improvements of the concepts and functions provided in this package.
Furthermore, in case you find some bugs or need additional (more flexible) functionality of parts of this package, please let me know:
https://github.com/HajkD/biomartr/issues
Getting Started with biomartr:
Users can also read the tutorials within (RStudio) :
# source the biomartr package
library(biomartr)
# look for all tutorials (vignettes) available in the biomartr package
# this will open your web browser
browseVignettes("biomartr")The current status of the package as well as a detailed history of the functionality of each version of biomartr can be found in the NEWS section.
Some bug fixes or new functionality will not be available on CRAN yet, but in the developer version here on GitHub. To download and install the most recent version of biomartr run:
# install the current version of biomartr on your system
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ropensci/biomartr")meta.retrieval() : Perform Meta-Genome Retieval from NCBI of species belonging to the same kingdom of life or to the same taxonomic subgroupmeta.retrieval.all() : Perform Meta-Genome Retieval from NCBI of the entire kingdom of lifegetMetaGenomes() : Retrieve metagenomes from NCBI GenbankgetMetaGenomeAnnotations() : Retrieve annotation *.gff files for metagenomes from NCBI GenbanklistMetaGenomes() : List available metagenomes on NCBI GenbankgetMetaGenomeSummary() : Helper function to retrieve the assembly_summary.txt file from NCBI genbank metagenomesclean.retrieval(): Format meta.retrieval outputlistGenomes() : List all genomes available on NCBI and ENSEMBL serverslistKingdoms() : list the number of available species per kingdom of life on NCBI and ENSEMBL serverslistGroups() : list the number of available species per group on NCBI and ENSEMBL serversgetKingdoms() : Retrieve available kingdoms of lifegetGroups() : Retrieve available groups for a kingdom of lifeis.genome.available() : Check Genome Availability NCBI and ENSEMBL serversgetCollection() : Retrieve a Collection: Genome, Proteome, CDS, RNA, GFF, Repeat Masker, AssemblyStatsgetGenome() : Download a specific genome stored on NCBI and ENSEMBL serversgetGenomeSet() : Genome Retrieval of multiple speciesgetProteome() : Download a specific proteome stored on NCBI and ENSEMBL serversgetProteomeSet() : Proteome Retrieval of multiple speciesgetCDS() : Download a specific CDS file (genome) stored on NCBI and ENSEMBL serversgetCDSSet() : CDS Retrieval of multiple speciesgetRNA() : Download a specific RNA file stored on NCBI and ENSEMBL serversgetRNASet() : RNA Retrieval of multiple speciesgetGFF() : Genome Annotation Retrieval from NCBI (*.gff) and ENSEMBL (*.gff3) serversgetGTF() : Genome Annotation Retrieval (*.gtf) from ENSEMBL serversgetRepeatMasker() : Repeat Masker TE Annotation RetrievalgetAssemblyStats() : Genome Assembly Stats Retrieval from NCBIgetKingdomAssemblySummary() : Helper function to retrieve the assembly_summary.txt files from NCBI for all kingdomsgetMetaGenomeSummary() : Helper function to retrieve the assembly_summary.txt files from NCBI genbank metagenomesgetSummaryFile() : Helper function to retrieve the assembly_summary.txt file from NCBI for a specific kingdomgetENSEMBLInfo() : Retrieve ENSEMBL info filegetGENOMEREPORT() : Retrieve GENOME_REPORTS file from NCBIread_genome() : Import genomes as Biostrings or data.table objectread_proteome() : Import proteome as Biostrings or data.table objectread_cds() : Import CDS as Biostrings or data.table objectread_gff() : Import GFF fileread_rna() : Import RNA fileread_rm() : Import Repeat Masker output fileread_assemblystats() : Import Genome Assembly Stats FilelistNCBIDatabases() : Retrieve a List of Available NCBI Databases for Downloaddownload.database() : Download a NCBI database to your local hard drivedownload.database.all() : Download a complete NCBI Database such as e.g. NCBI nr to your local hard drivebiomart() : Main function to query the BioMart databasegetMarts() : Retrieve All Available BioMart DatabasesgetDatasets() : Retrieve All Available Datasets for a BioMart DatabasegetAttributes() : Retrieve All Available Attributes for a Specific DatasetgetFilters() : Retrieve All Available Filters for a Specific DatasetorganismBM() : Function for organism specific retrieval of available BioMart marts and datasetsorganismAttributes() : Function for organism specific retrieval of available BioMart attributesorganismFilters() : Function for organism specific retrieval of available BioMart filtersgetGO() : Function to retrieve GO terms for a given set of genes# On Windows, this won't work - see ?build_github_devtools
install_github("HajkD/biomartr", build_vignettes = TRUE, dependencies = TRUE)
# When working with Windows, first you need to install the
# R package: rtools -> install.packages("rtools")
# Afterwards you can install devtools -> install.packages("devtools")
# and then you can run:
devtools::install_github("HajkD/biomartr", build_vignettes = TRUE, dependencies = TRUE)
# and then call it from the library
library("biomartr", lib.loc = "C:/Program Files/R/R-3.1.1/library")Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.