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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 detaileddocumentation here.

Please citebiomartr if it was helpful for your research. This will allow me tocontinue 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 encodedon 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 theretrieval process of this information on a meta-genomic scale, thebiomartr package provides interface functions for genomic sequence retrieval and functional annotation retrieval. The major aim ofbiomartr is to facilitate computational reproducibility and large-scale handling of genomic data for (meta-)genomic analyses.In addition,biomartr aims to address thegenome version crisis. Withbiomartr users can now control and be informedabout the genome versions they retrieve automatically. Many large scale genomics studies lack this informationand thus, reproducibility and data interpretation become nearly impossible when documentation of genome version informationgets 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

• NCBI RefSeq
• NCBI Genbank
• ENSEMBL
• ENSEMBLGENOMES (as of April 2019 -ENSEMBL andENSEMBLGENOMES were joined - seedetails here)
• UniProt

Furthermore, an interface to theEnsembl Biomart database allows users to retrieve functional annotation for genomic loci using a novel and organism centric search strategy. In addition, users candownload entire databases such as

• NCBI RefSeq
• NCBI nr
• NCBI nt
• NCBI Genbank
• ENSEMBL

with only one command.

The main difference between theBiomaRt package and thebiomartr package is thatbiomartr extends thefunctional annotation retrieval procedure ofBiomaRt andin 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 asNCBI nr etc.

Please consult theTutorials section for more details.

In the context of functional annotation retrieval thebiomartr 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 theBiomaRt 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 dedicatedan entire vignette to compare theBiomaRt andbiomartr package functionality in the context ofFunctional 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 improvebiomartr in the best possible way. Many many thanks in advance.

Thebiomartr package relies on someBioconductor tools and thus requiresinstallation of the following packages:

# Install core Bioconductor packagesif (!requireNamespace("BiocManager"))    install.packages("BiocManager")BiocManager::install()# Install package dependenciesBiocManager::install("Biostrings")BiocManager::install("biomaRt")

Now users can installbiomartr from CRAN:

# install biomartr 1.0.11 from CRANinstall.packages("biomartr",dependencies=TRUE)# install the developer version containing the newest featuresBiocManager::install("ropensci/biomartr")

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install r-biomartr

and update with:

conda update r-biomartr

or use the docker container:

docker pull quay.io/biocontainers/r-biomartr:<tag>

(checkr-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 fileand was generated using the same genome assembly version. One aspect of why genomics studiesfail in computational and biological reproducibility is that it is not clear whether CDS, proteome, RNA, GFF, etc filesused 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 retrievegenome file collections using thebiomartr functiongetCollection()and attach the corresponding output as Supplementary Datato the respective genomics study to ensure computational and biological reproducibility.

# download collection for Saccharomyces cerevisiaebiomartr::getCollection(db="refseq",organism="Saccharomyces cerevisiae")

Internally, thegetCollection() function will now generate a folder namedrefseq/Collection/Saccharomyces_cerevisiaeand will store all genome and annotation files forSaccharomyces cerevisiae in the same folder.In addition, the exact genoem and annotation version will be logged in thedoc folder.

Internally, a text file nameddoc_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.txtOrganism Name: Saccharomyces_cerevisiaeDatabase: NCBI refseqURL: ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/146/045/GCF_000146045.2_R64/GCF_000146045.2_R64_assembly_stats.txtDownload_Date: Wed Jun 27 15:21:51 2018refseq_category: reference genomeassembly_accession: GCF_000146045.2bioproject: PRJNA128biosample: NAtaxid: 559292infraspecific_name: strain=S288Cversion_status: latestrelease_type: Majorgenome_rep: Fullseq_rel_date: 2014-12-17submitter: Saccharomyces Genome Database

In an ideal world this reference file could then be included as supplementary information in anylife science publication that relies on genomic information so thatreproducibility of experiments and analyses becomes achievable.

Download all mammalian vertebrate genomes fromNCBI RefSeq via:

# download all vertebrate genomesmeta.retrieval(kingdom="vertebrate_mammalian",db="refseq",type="genome")

All geneomes are stored in the folder named according to the kingdom.In this casevertebrate_mammalian. Alternatively, users can specifytheout.folder argument to define a custom output folder path.

Please findall FAQs here.

I would be very happy to learn more about potential improvements of the concepts and functionsprovided in this package.

Furthermore, in case you find some bugs or need additional (more flexible) functionality of partsof this package, please let me know:

https://github.com/HajkD/biomartr/issues

Getting Started withbiomartr:

• NCBI Database Retrieval
• Genomic Sequence Retrieval
• Meta-Genome Retrieval
• Functional Annotation
• BioMart Examples

Users can also read the tutorials within (Posit (former RStudio)) :

# source the biomartr packagelibrary(biomartr)# look for all tutorials (vignettes) available in the biomartr package# this will open your web browserbrowseVignettes("biomartr")

The current status of the package as well as a detailed history of the functionality of each version ofbiomartr can be found in theNEWS 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 ofbiomartr run:

# install the current version of biomartr on your systemif (!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 subgroup
• meta.retrieval.all() : Perform Meta-Genome Retieval from NCBI of the entire kingdom of life
• getMetaGenomes() : Retrieve metagenomes from NCBI Genbank
• getMetaGenomeAnnotations() : Retrieve annotation *.gff files for metagenomes from NCBI Genbank
• listMetaGenomes() : List available metagenomes on NCBI Genbank
• getMetaGenomeSummary() : Helper function to retrieve the assembly_summary.txt file from NCBI genbank metagenomes
• clean.retrieval(): Format meta.retrieval output

• listGenomes() : List all genomes available on NCBI and ENSEMBL servers
• listKingdoms() : list the number of available species per kingdom of life on NCBI and ENSEMBL servers
• listGroups() : list the number of available species per group on NCBI and ENSEMBL servers
• getKingdoms() : Retrieve available kingdoms of life
• getGroups() : Retrieve available groups for a kingdom of life
• is.genome.available() : Check Genome Availability NCBI and ENSEMBL servers
• getCollection() : Retrieve a Collection: Genome, Proteome, CDS, RNA, GFF, Repeat Masker, AssemblyStats
• getGenome() : Download a specific genome stored on NCBI and ENSEMBL servers
• getGenomeSet() : Genome Retrieval of multiple species
• getProteome() : Download a specific proteome stored on NCBI and ENSEMBL servers
• getProteomeSet() : Proteome Retrieval of multiple species
• getCDS() : Download a specific CDS file (genome) stored on NCBI and ENSEMBL servers
• getCDSSet() : CDS Retrieval of multiple species
• getRNA() : Download a specific RNA file stored on NCBI and ENSEMBL servers
• getRNASet() : RNA Retrieval of multiple species
• getGFF() : Genome Annotation Retrieval from NCBI (*.gff) and ENSEMBL (*.gff3) servers
• getGTF() : Genome Annotation Retrieval (*.gtf) from ENSEMBL servers
• getRepeatMasker() : Repeat Masker TE Annotation Retrieval
• getAssemblyStats() : Genome Assembly Stats Retrieval from NCBI
• getKingdomAssemblySummary() : Helper function to retrieve the assembly_summary.txt files from NCBI for all kingdoms
• getMetaGenomeSummary() : Helper function to retrieve the assembly_summary.txt files from NCBI genbank metagenomes
• getSummaryFile() : Helper function to retrieve the assembly_summary.txt file from NCBI for a specific kingdom
• getENSEMBLInfo() : Retrieve ENSEMBL info file
• getGENOMEREPORT() : Retrieve GENOME_REPORTS file from NCBI

• read_genome() : Import genomes as Biostrings or data.table object
• read_proteome() : Import proteome as Biostrings or data.table object
• read_cds() : Import CDS as Biostrings or data.table object
• read_gff() : Import GFF file
• read_rna() : Import RNA file
• read_rm() : Import Repeat Masker output file
• read_assemblystats() : Import Genome Assembly Stats File

• listNCBIDatabases() : Retrieve a List of Available NCBI Databases for Download
• download.database() : Download a NCBI database to your local hard drive
• download.database.all() : Download a complete NCBI Database such as e.g.NCBI nr to your local hard drive

• biomart() : Main function to query the BioMart database
• getMarts() : Retrieve All Available BioMart Databases
• getDatasets() : Retrieve All Available Datasets for a BioMart Database
• getAttributes() : Retrieve All Available Attributes for a Specific Dataset
• getFilters() : Retrieve All Available Filters for a Specific Dataset
• organismBM() : Function for organism specific retrieval of available BioMart marts and datasets
• organismAttributes() : Function for organism specific retrieval of available BioMart attributes
• organismFilters() : Function for organism specific retrieval of available BioMart filters

• getGO() : Function to retrieve GO terms for a given set of genes

# On Windows, this won't work - see ?build_github_devtoolsinstall_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 librarylibrary("biomartr",lib.loc="C:/Program Files/R/R-3.1.1/library")

Please note that this project is released with aContributor Code of Conduct. By participating in this project you agree to abide by its terms.