Package 'biomartr'

Description

This package interacts with a suite of web Application Programming Interfaces and FTP sites to perform automated genomic data retieval and annotation information retrieval.

About

To automate the retrieval process on a meta-genomic scale, this package provides useful 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 detail, biomartr aims to provide users with an easy to use framework to obtain genome, proteome, CDS, GFF (annotation), genome assembly quality, and metagenome project data. Furthermore, an interface to the Ensembl Biomart database allows users to retrieve functional annotation for genomic loci. Users can download entire databases such as

• NCBI RefSeq

• NCBI nr

• NCBI nt

• NCBI Genbank

• NCBI nt

• Ensembl

• Ensembl Genomes

• UniProt

Author(s)

Hajk-Georg Drost [email protected]

See Also

Useful links:

• https://docs.ropensci.org/biomartr/

• https://github.com/ropensci/biomartr

• Report bugs at https://github.com/ropensci/biomartr/issues

Description

This function takes a set of gene ids and the biomart specifications and performs a biomart query for the given set of gene ids.

Usage

biomart(genes, mart, dataset, attributes, filters, mute_citation = FALSE, ...)

Arguments

Details

This function is the main query function of the biomartr package.

It enables to fastly access annotations of a given gene set based on the biomaRt package implemented by Steffen Durinck et al.

Value

A data.table storing the initial query gene vector in the first column, the output gene vector in the second column, and all attributes in the following columns.

Author(s)

Hajk-Georg Drost

See Also

Other biomaRt: getAttributes(), getDatasets(), getMarts(), organismBM(), organismFilters()

Examples

## Not run: 
# 1) select a mart
getMarts()

# we will select mart 'plants_mart' and search for available datasets
getDatasets(mart = "plants_mart")

# we choose dataset 'athaliana_eg_gene' and run biomart()
# using mart: 'plants_mart', dataset: "athaliana_eg_gene"
# attributes: c("start_position","end_position","description")
# for an example gene set of Arabidopsis thaliana:
# c("AT1G06090", "AT1G06100", "AT1G06110", "AT1G06120",
#    "AT1G06130", "AT1G06200")

biomart(genes      = c("AT1G06090", "AT1G06100",
                       "AT1G06110", "AT1G06120",
                       "AT1G06130", "AT1G06200"),
        mart       = "plants_mart",
        dataset    = "athaliana_eg_gene",
        attributes = c("start_position","end_position","description"),
        filters    = "ensembl_gene_id")

## End(Not run)

Description

Get directory to store back end files like kingdom summaries etc

Usage

cachedir(non_temp_cache = "~/.biomartr_cache_dir.rds")

Arguments

Value

reads the rds file, and returns the path for local cache, if not existing, use tempdir().

See Also

Other cachedir: cachedir_set()

Examples

cachedir()

Description

Set directory to store back end files like kingdom summaries etc

Usage

cachedir_set(path)

Arguments

Value

invisible(NULL), only save the file to path location

See Also

Other cachedir: cachedir()

Examples

# By default it is tempdir()
cachedir()
# cachedir_set("~/Bio_data/biomartr_cache/")
cachedir()

Description

Some annotation files include lines with character lengths greater than 65000. This causes problems when trying to import such annotation files into R using import. To overcome this issue, this function screens for such lines in a given annotation file and removes these lines so that import can handle the file.

Usage

check_annotation_biomartr(annotation_file, remove_annotation_outliers = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
# download an example annotation file from NCBI RefSeq
Ath_path <- biomartr::getGFF(organism = "Arabidopsis thaliana")
# run annotation file check on the downloaded file
biomartr::check_annotation_biomartr(Ath_path)
# several outlier lines were detected, thus we re-run the
# function using 'remove_annotation_outliers = TRUE'
# to remove the outliers and overwrite the file
biomartr::check_annotation_biomartr(Ath_path, remove_annotation_outliers = TRUE)

## End(Not run)

Description

This function allows users to download a database selected by listDatabases to their local hard drive.

Usage

download.database(db, path = "database")

Arguments

Details

This function downloads large databases to your hard drive. For this purpose a folder named database (default) is created and the correspondning database then stored in this folder.

Value

File path to the downloaded database file.

Author(s)

Hajk-Georg Drost

See Also

download.database.all, listDatabases

Examples

## Not run: 
  # search for available NCBI nr databases
  listNCBIDatabases(db = "nr")
  # select NCBI nr version 27 =  "nr.27.tar.gz"
  # and download it to your hard drive
  # -> please note that large databases take some time for download!
  download.database(db = "nr.27.tar.gz")

## End(Not run)

Description

The download.database functions allows users to retrieve individual packages of a NCBI database. This function is designed to retrieve the entire database selected by the users (hence all packages corresponding to this database).

Usage

download.database.all(db, path = NULL)

Arguments

Value

A character vector storing the file paths of the downloaded databases.

Author(s)

Hajk-Georg Drost

See Also

download.database, listNCBIDatabases

Examples

## Not run: 
# search for available NCBI databases
  listNCBIDatabases(db = "all")
# choose database NCBI nr and download compelete database
  download.database.all(db = "nr", path = "nr")

## End(Not run)

Description

Retrieve a list of available databases on ENSEMBL for which get.ensembl.info can be retrieved.

Usage

ensembl_divisions()

Author(s)

Hajk-Georg Drost

Examples

ensembl_divisions()

Description

This function interfaces with the ENSEMBL API (https://rest.ensembl.org/info/species?content-type=application/json) and internally stores the output to use this information for subsequent retrieval function calls.

Usage

get.ensembl.info(update = FALSE, division)

Arguments

Author(s)

Hajk-Georg Drost

See Also

ensembl_divisions, getKingdomAssemblySummary, getENSEMBLInfo

Examples

## Not run: 
# Look at available ENSEMBL division options
ensembl_divisions()
# Retrieve available information for EnsemblVertebrates
example <- get.ensembl.info(division = "EnsemblVertebrates")
example
# Update information file stored in the tempdir() folder.
example_update <- get.ensembl.info(division = "EnsemblVertebrates", update = TRUE)
example_update

## End(Not run)

Description

Main genome assembly stats retrieval function for an organism of interest. By specifying the scientific name of an organism of interest the corresponding genome assembly stats file storing the assembly statistics of the organism of interest can be downloaded and stored locally. Genome assembly stats files can be retrieved from several databases.

Usage

getAssemblyStats(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  type = "download",
  path = file.path("_ncbi_downloads", "genomeassembly_stats"),
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

to retrieve available scientific names of organisms and creates a directory '_ncbi_downloads/genomeassembly_stats' to store the Genome Assembly Stats of interest as text file for future processing. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomeassembly_stats' folder and is accessible within the workspace, no download process will be performed.

An example genome assembly stats file can be found here: ftp://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/001/405/ GCF_000001405.36_GRCh38.p10/GCF_000001405.36_GRCh38.p10_assembly_stats.txt.

Value

File path to downloaded genome assembly stats file.

Author(s)

Hajk-Georg Drost

See Also

getGenome, getProteome, getCDS, getGFF, getRNA, getCollection, meta.retrieval, read_assemblystats

Examples

## Not run: 
# download the genome assembly stats file of Saccharomyces cerevisiae
# from NCBI RefSeq
# and store the corresponding genome file in
# '_ncbi_downloads/genomeassembly_stats'
file_path <- getAssemblyStats( db = "refseq",
                 organism = "Saccharomyces cerevisiae",
                 path = file.path("_ncbi_downloads","genomeassembly_stats"))
# import the raw file as it is downloaded
Scerevisiae.stats <- read_assemblystats(file_path, type = "raw")

# download the genome assembly stats file of Saccharomyces cerevisiae
# from NCBI RefSeq
# and import overall statistics of the genome assembly
Scerevisiae.stats.import <- getAssemblyStats( db = "refseq",
                 organism = "Saccharomyces cerevisiae",
                 type = "import",
                 path = file.path("_ncbi_downloads","genomeassembly_stats"))

## End(Not run)

Description

This function queries the BioMart Interface and returns a table storing all available attributes for a specific dataset.

Usage

getAttributes(mart, dataset, mute_citation = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

Other biomaRt: biomart(), getDatasets(), getMarts(), organismBM(), organismFilters()

Examples

## Not run: 
# search for available datasets
getMarts()

# choose database (mart): ENSEMBL_MART_ENSEMBL
# and get a table of all available datasets from this BioMart database
head(getDatasets(mart = "ENSEMBL_MART_ENSEMBL"), 10)

# choose dataset: "hsapiens_gene_ensembl"
head(getAttributes(mart = "ENSEMBL_MART_ENSEMBL",
                   dataset = "hsapiens_gene_ensembl") , 5)

## End(Not run)

Description

A wrapper to all bio getters, selected with 'type' argument

Usage

getBio(
  db = "refseq",
  organism,
  type,
  reference = FALSE,
  release = NULL,
  gunzip = FALSE,
  update = FALSE,
  skip_bacteria = TRUE,
  path = paste0("set_", toupper(type)),
  remove_annotation_outliers = FALSE,
  analyse_genome = FALSE,
  assembly_type = "toplevel",
  format = "gff3",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getCDS(), getCollection(), getGFF(), getGenome(), getProteome(), getRNA()

Description

Usually you want to use one of the specific set extractors

Usage

getBioSet(
  db = "refseq",
  organisms,
  set_type,
  reference = FALSE,
  release = NULL,
  gunzip = TRUE,
  update = FALSE,
  skip_bacteria = TRUE,
  path = paste0("set_", toupper(set_type)),
  remove_annotation_outliers = FALSE,
  assembly_type = "toplevel",
  format = "gff3",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

getBio

Other getBioSet: getCDSSet(), getCollectionSet(), getGFFSet(), getGenomeSet(), getProteomeSet(), getRNASet()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

Main retrieval function for coding sequences (CDS) of an organism of interest. By specifying the scientific name of an organism of interest the corresponding fasta-file storing the CDS information for the organism of interest can be downloaded and stored locally. CDS files can be retrieved from several databases.

Usage

getCDS(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  gunzip = FALSE,
  path = file.path("_ncbi_downloads", "CDS"),
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCollection(), getGFF(), getGenome(), getProteome(), getRNA()

Other cds: getCDSSet(), read_cds()

Examples

## Not run: 
# download the genome of Arabidopsis thaliana from refseq
# and store the corresponding genome CDS file in '_ncbi_downloads/CDS'
file_path <- getCDS( db       = "refseq",
             organism = "Arabidopsis thaliana",
             path     = file.path("_ncbi_downloads","CDS"))

Ath_CDS <- read_cds(file_path, format = "fasta")


## End(Not run)

Description

Main CDS retrieval function for a set of organism of interest. By specifying the scientific names of the organisms of interest the corresponding fasta-files storing the CDS of the organisms of interest will be downloaded and stored locally. CDS files can be retrieved from several databases.

Usage

getCDSSet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  gunzip = TRUE,
  update = FALSE,
  path = "set_CDS"
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCollectionSet(), getGFFSet(), getGenomeSet(), getProteomeSet(), getRNASet()

Other cds: getCDS(), read_cds()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

Main collection retrieval function for an organism of interest. By specifying the scientific name of an organism of interest a collection consisting of the genome file, proteome file, CDS file, RNA file, GFF file, Repeat Masker file, AssemblyStats file of the organism of interest can be downloaded and stored locally. Collections can be retrieved from several databases. For full set of collection elements, see: biomartr:::supported_biotypes(db)

Usage

getCollection(
  db = "refseq",
  organism,
  reference = TRUE,
  skip_bacteria = TRUE,
  release = NULL,
  assembly_type = "toplevel",
  analyse_genome = FALSE,
  remove_annotation_outliers = FALSE,
  gunzip = FALSE,
  path = file.path("_db_downloads", "collections"),
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getGFF(), getGenome(), getProteome(), getRNA()

Other collection: getCollectionSet()

Examples

## Not run: 
# download the collection of Homo sapiens from refseq
# and store the corresponding genome file in '_ncbi_downloads/collection'
 Hsap_collection <- getCollection( db       = "refseq",
             organism = "Homo sapiens",
             path = file.path("_db_downloads","collections"))
# download the collection of Homo sapiens from genbank
# and store the corresponding genome file in '_ncbi_downloads/collection'
 Hsap_collection <- getCollection( db       = "genbank",
             organism = "Homo sapiens",
             path = file.path("_db_downloads","collections"))
# download the collection of Homo sapiens from ensembl
# and store the corresponding genome file in '_ncbi_downloads/collection'
 Hsap_collection <- getCollection( db       = "ensembl",
             organism = "Homo sapiens",
             path = file.path("_db_downloads","collections"))

## End(Not run)

Description

Main collection retrieval function for an organism of interest. By specifying the scientific name of an organism of interest a collection consisting of the genome file, proteome file, CDS file, RNA file, GFF file, Repeat Masker file, AssemblyStats file of the organism of interest can be downloaded and stored locally. Collections can be retrieved from several databases.

Usage

getCollectionSet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  skip_bacteria = TRUE,
  gunzip = TRUE,
  update = FALSE,
  remove_annotation_outliers = TRUE,
  path = "set_collections",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCDSSet(), getGFFSet(), getGenomeSet(), getProteomeSet(), getRNASet()

Other collection: getCollection()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

This funcion queries the BioMart API and returns a table storing all available datasets for a selected BioMart databases.

Usage

getDatasets(mart, mute_citation = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

Other biomaRt: biomart(), getAttributes(), getMarts(), organismBM(), organismFilters()

Examples

## Not run: 
# search for available datasets
# getMarts()
# choose database: "ENSEMBL_MART_ENSEMBL"
head(getDatasets("ENSEMBL_MART_ENSEMBL"), 10)

## End(Not run)

Description

Backend function for retrieving files sequence and annotation files from the ENSEMBL ftp server

Usage

getENSEMBL(
  organism,
  type = "dna",
  id.type = "toplevel",
  release = NULL,
  path,
  format
)

Arguments

Value

either a character path to downloaded file, or a logical FALSE, specifying failure.

Author(s)

Hajk-Georg Drost

Description

This function downloads gff files of query organisms from ENSEMBL.

Usage

getENSEMBL.gtf(organism, type = "dna", path, release = NULL)

Arguments

Value

character filepath to download file, returns FALSE if failed.

Author(s)

Hajk-Georg Drost

Description

This function downloads gff files of query organisms from ENSEMBL.

Usage

getENSEMBL.Seq(
  organism,
  type = "dna",
  id.type = "toplevel",
  release = NULL,
  path
)

Arguments

Value

either a character path to downloaded file, or a logical FALSE, specifying failure.

Author(s)

Hajk-Georg Drost

Description

Retrieve species and genome information from http://rest.ensemblgenomes.org/info/species?content-type=application/json/.

Usage

getENSEMBLGENOMESInfo()

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
info.file <- getENSEMBLGENOMESInfo()
info.file

## End(Not run)

Description

Retrieve species and genome information from http://rest.ensembl.org/info/species?content-type=application/json/.

Usage

getENSEMBLInfo(update = FALSE, divisions = ensembl_divisions())

Arguments

Value

a tibble table storing info for all available ENSEMBL divisions.

Author(s)

Hajk-Georg Drost

See Also

ensembl_divisions, get.ensembl.info, getKingdomAssemblySummary

Examples

## Not run: 
# look at available divisions
ensembl_divisions()
# retrieve information for all ENSEMBL divisions at once
test <- getENSEMBLInfo()
test
# retrieve information for a particular ENSEMBL division (e.g. EnsemblVertebrates)
test_vertebrates <- get.ensembl.info(update = TRUE, division = "EnsemblVertebrates")
test_vertebrates

## End(Not run)

Description

This funcion queries the BioMart API and returns a table storing all available filters for a specific dataset.

Usage

getFilters(mart, dataset, mute_citation = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

getMarts, getDatasets, getAttributes, organismBM, organismFilters, organismAttributes

Examples

## Not run: 
# search for available datasets
# getMarts()
# choose database (mart): "ENSEMBL_MART_ENSEMBL"
# head(getDatasets(mart = "ENSEMBL_MART_ENSEMBL"), 10)
# choose dataset: "hsapiens_gene_ensembl"
head(getFilters(mart = "ENSEMBL_MART_ENSEMBL",
                dataset = "hsapiens_gene_ensembl") , 5)

## End(Not run)

Description

Main genome retrieval function for an organism of interest. By specifying the scientific name of an organism of interest the corresponding fasta-file storing the genome of the organism of interest can be downloaded and stored locally. Genome files can be retrieved from several databases. In addition, the genome summary statistics for the retrieved species is stored locally to provide users with insights regarding the genome assembly quality (see summary_genome for details). This is useful when comparing genomes with large difference in genome assembly qualities.

Usage

getGenome(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  gunzip = FALSE,
  path = file.path("_ncbi_downloads", "genomes"),
  assembly_type = "toplevel",
  mute_citation = FALSE,
  analyse_genome = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getCollection(), getGFF(), getProteome(), getRNA()

Other genome: getGenomeSet(), read_genome()

Description

Retrieves NCBI GENOME_REPORTS file from ftp://ftp.ncbi.nlm.nih.gov/genomes/GENOME_REPORTS/overview.txt.

Usage

getGENOMEREPORT(
  local_file = file.path(cachedir(), "_ncbi_downloads", "overview.txt")
)

Arguments

Value

a tibble object with the report

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
report <- getGENOMEREPORT()
report

## End(Not run)

Description

Main genome retrieval function for a set of organism of interest. By specifying the scientific names of the organisms of interest the corresponding fasta-files storing the genome of the organisms of interest will be downloaded and stored locally. Genome files can be retrieved from several databases.

Usage

getGenomeSet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  skip_bacteria = TRUE,
  gunzip = TRUE,
  update = FALSE,
  path = "set_genomes",
  assembly_type = "toplevel",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCDSSet(), getCollectionSet(), getGFFSet(), getProteomeSet(), getRNASet()

Other genome: getGenome(), read_genome()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

Main retrieval function for GFF files of an organism of interest. By specifying the scientific name of an organism of interest the corresponding gff file storing the annotation for the organism of interest can be downloaded and stored locally. GFF files can be retrieved from several databases.

Usage

getGFF(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  gunzip = FALSE,
  remove_annotation_outliers = FALSE,
  path = file.path("_ncbi_downloads", "annotation"),
  mute_citation = FALSE,
  format = "gff3"
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getCollection(), getGenome(), getProteome(), getRNA()

Other gff: getGFFSet(), read_gff()

Examples

## Not run: 
# download the annotation of Arabidopsis thaliana from refseq
# and store the corresponding genome file in '_ncbi_downloads/annotation'
Athal_gff <- getGFF( db       = "refseq",
               organism = "Arabidopsis thaliana",
               path = file.path("_ncbi_downloads","annotation"),
               remove_annotation_outliers = TRUE)
Athal_gff_import <- read_gff(Athal_gff)


# download the genome of Arabidopsis thaliana from genbank
# and store the corresponding genome file in '_ncbi_downloads/annotation'
Athal_gff <- getGFF( db       = "genbank",
               organism = "Arabidopsis thaliana",
               path = file.path("_ncbi_downloads","annotation"),
               remove_annotation_outliers = TRUE)
Athal_gff_import <- read_gff(Athal_gff)

# download the genome of Homo sapiens from ensembl
# and store the corresponding genome file in '_ncbi_downloads/annotation'
Hsap_gff <- getGFF( db       = "ensembl",
               organism = "Homo sapiens",
               path = file.path("_ncbi_downloads","annotation"),
               remove_annotation_outliers = TRUE)
Hsap_gff_import <- read_gff(Hsap_gff)


## End(Not run)

Description

Main GFF retrieval function for a set of organism of interest. By specifying the scientific names of the organisms of interest the corresponding fasta-files storing the GFF of the organisms of interest will be downloaded and stored locally. GFF files can be retrieved from several databases.

Usage

getGFFSet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  skip_bacteria = TRUE,
  gunzip = TRUE,
  remove_annotation_outliers = FALSE,
  update = FALSE,
  format = "gff3",
  path = "set_GFF",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCDSSet(), getCollectionSet(), getGenomeSet(), getProteomeSet(), getRNASet()

Other gff: getGFF(), read_gff()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

This function takes a gene id as character vector from a given query organism and returns the corresponding GO terms and additional GO information.

Usage

getGO(organism, genes, filters, ...)

Arguments

Details

This function takes the scientific name of a query organism, a set of genes for which GO terms and additional information shall be retrieved, and a filter argument that specifies the attribute for the query genes.

Author(s)

Hajk-Georg Drost

See Also

biomart, organismFilters, organismBM, getBM, getMarts, getDatasets, getFilters

Examples

## Not run:  
GO_tbl <- getGO(organism = "Arabidopsis thaliana", 
                genes    = c("AT1G06090", "AT1G06100"),
                filters  = "ensembl_gene_id")

# look at the result
head(GO_tbl)

## End(Not run)

Description

A short list of available groups for a kingdom of life.

Usage

getGroups(db = "refseq", kingdom)

Arguments

Author(s)

Hajk-Georg Drost

See Also

meta.retrieval, getGenome, getProteome, getCDS, getKingdoms

Examples

# get possible kigdom names
getKingdoms(db = "refseq")
## Not run: 
# retrieve subgroups for vertebrate_mammalian available from refseq
getGroups(db = "refseq", kingdom = "vertebrate_mammalian")

# get possible kigdom names
getKingdoms(db = "genbank")
# retrieve subgroups for vertebrate_mammalian available from genbank
getGroups(db = "genbank", kingdom = "vertebrate_mammalian")

## End(Not run)

Description

Main retrieval function for GTF files of an organism of interest. By specifying the scientific name of an organism of interest the corresponding GTF file storing the annotation for the organism of interest can be downloaded and stored locally. GTF files can be retrieved from several databases.

Usage

getGTF(
  db = "ensembl",
  organism,
  remove_annotation_outliers = FALSE,
  path = file.path("ensembl", "annotation"),
  release = NULL,
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getCollection(), getGenome(), getProteome(), getRNA()

Other gff: getGFFSet(), read_gff()

Examples

## Not run: 
# download the annotation of Homo sapiens from ensembl
# and store the corresponding genome file in 'ensembl/annotation'
getGTF(db            = "ensembl",
       organism      = "Homo sapiens",
       path          = file.path("ensembl","annotation"))

getGTF(db            = "ensembl",
       organism      = "Homo sapiens",
       path          = file.path("ensembl","annotation"),
       assembly_type = "primary_assembly")


## End(Not run)

Description

Retrieval function of the assembly_summary.txt file from NCBI for all kingdoms. The assembly_summary.txt files store available species on NCBI.

Usage

getKingdomAssemblySummary(
  db,
  skip_bacteria = TRUE,
  file = assemblies_info_path(db)
)

Arguments

Author(s)

Hajk-Georg Drost

See Also

getSummaryFile, getMetaGenomeSummary, get.ensembl.info

Examples

## Not run: 
# This example will run the default version of this function
# whereby information for Bacteria are not downloaded
test <- getKingdomAssemblySummary(db = "genbank", skip_bacteria = TRUE)
test
# Users can then retrieve information for Bacteria by skip_bacteria = FALSE
test2 <- getKingdomAssemblySummary(db = "genbank", skip_bacteria = FALSE)
test2

## End(Not run)

Description

A short list of available kingdoms of life

Usage

getKingdoms(db = "refseq")

Arguments

Author(s)

Hajk-Georg Drost

See Also

meta.retrieval, getGenome, getProteome, getCDS, getGroups

Examples

# retrieve kingdoms available from refseq
getKingdoms(db = "refseq")

# retrieve kingdoms available from genbank
getKingdoms(db = "genbank")

Description

This funcion queries the Ensembl Biomart API and returns a table storing information about all available Ensembl Biomart databases.

Usage

getMarts(update = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

Other biomaRt: biomart(), getAttributes(), getDatasets(), organismBM(), organismFilters()

Examples

## Not run: 
# get a table of all available databases from Ensembl Biomart
getMarts()
 
## End(Not run)

Description

Retrieve available annotation *.gff files for metagenomes from NCBI Genbank. NCBI Genbank allows users to download entire metagenomes and their annotations of several metagenome projects. This function downloads available metagenomes that can then be downloaded via getMetaGenomes.

Usage

getMetaGenomeAnnotations(
  name,
  path = file.path("_ncbi_downloads", "metagenome", "annotations")
)

Arguments

Author(s)

Hajk-Georg Drost

See Also

getMetaGenomes, listMetaGenomes, getGFF

Examples

## Not run: 
# Frist, retrieve a list of available metagenomes
listMetaGenomes()

# Now, retrieve the 'human gut metagenome'
getMetaGenomeAnnotations(name = "human gut metagenome")

## End(Not run)

Description

Retrieve available metagenomes from NCBI Genbank. NCBI Genbank allows users to download entire metagenomes of several metagenome projects. This function downloads available metagenomes that can then be downloaded via getMetaGenomes.

Usage

getMetaGenomes(name, path = file.path("_ncbi_downloads", "metagenome"))

Arguments

Author(s)

Hajk-Georg Drost

See Also

getMetaGenomeAnnotations, listMetaGenomes

Examples

## Not run: 
# Frist, retrieve a list of available metagenomes
listMetaGenomes()

# Now, retrieve the 'human gut metagenome'
getMetaGenomes(name = "human gut metagenome")

## End(Not run)

Description

Retrieval function of the assembly_summary.txt file from NCBI genbank metagenomes. This files stores all available metagenome projects on NCBI Genbank.

Usage

getMetaGenomeSummary(
  local_file = file.path(cachedir(), "assembly_summary_metagenomes_genbank.txt")
)

Arguments

Author(s)

Hajk-Georg Drost

See Also

getKingdomAssemblySummary, getSummaryFile

Examples

## Not run: 
meta.summary <- getMetaGenomeSummary()
meta.summary

## End(Not run)

Description

Main proteome retrieval function for an organism of interest. By specifying the scientific name of an organism of interest the corresponding fasta-file storing the proteome of the organism of interest can be downloaded and stored locally. Proteome files can be retrieved from several databases.

Usage

getProteome(
  db = "refseq",
  organism,
  reference = TRUE,
  skip_bacteria = TRUE,
  release = NULL,
  gunzip = FALSE,
  update = TRUE,
  path = file.path("_ncbi_downloads", "proteomes"),
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory '_ncbi_downloads/proteomes' to store the proteome of interest as fasta file for future processing.

Value

File path to downloaded proteome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getCollection(), getGFF(), getGenome(), getRNA()

Other proteome: getProteomeSet(), read_proteome()

Examples

## Not run: 
# download the proteome of Arabidopsis thaliana from NCBI RefSeq
# and store the corresponding proteome file in '_ncbi_downloads/refseq/proteomes'
file_path <- getProteome( db       = "refseq",
             organism = "Arabidopsis thaliana",
             path     = file.path("_ncbi_downloads","refseq","proteomes") )
# import proteome into R session
Ath_proteome <- read_proteome(file_path, format = "fasta")

# download the proteome of Arabidopsis thaliana from NCBI Genbank
# and store the corresponding proteome file in '_ncbi_downloads/genbank/proteomes'
file_path <- getProteome( db       = "genbank",
             organism = "Arabidopsis thaliana",
             path     = file.path("_ncbi_downloads","genbank","proteomes") )
# import proteome into R session
Ath_proteome <- read_proteome(file_path, format = "fasta")

# and store the corresponding proteome file in '_downloads/uniprot/proteomes'
file_path <- getProteome( db       = "uniprot",
             organism = "Arabidopsis thaliana",
             path     = file.path("_downloads","uniprot","proteomes") )
# import proteome into R session
Ath_proteome <- read_proteome(file_path, format = "fasta")

# download the proteome of Arabidopsis thaliana from ENSEMBL
# and store the corresponding proteome file in '_downloads/ensembl/proteomes'
file_path <- getProteome( db       = "ensembl",
             organism = "Arabidopsis thaliana",
             path     = file.path("_downloads","ensembl","proteomes") )
# import proteome into R session
Ath_proteome <- read_proteome(file_path, format = "fasta")

## End(Not run)

Description

Main proteome retrieval function for a set of organism of interest. By specifying the scientific names of the organisms of interest the corresponding fasta-files storing the proteome of the organisms of interest will be downloaded and stored locally. proteome files can be retrieved from several databases.

Usage

getProteomeSet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  skip_bacteria = TRUE,
  gunzip = TRUE,
  update = FALSE,
  path = "set_proteomes",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCDSSet(), getCollectionSet(), getGFFSet(), getGenomeSet(), getRNASet()

Other proteome: getProteome(), read_proteome()

Examples

## Not run: 
# download the proteomes of three different species at the same time
#### Database: NCBI RefSeq
file_paths <- getProteomeSet(db = "refseq", organisms = c("Arabidopsis thaliana",
                                      "Arabidopsis lyrata",
                                       "Capsella rubella"))
# look at file paths
file_paths

#### Database: NCBI Genbank
file_paths <- getProteomeSet(db = "genbank", organisms = c("Arabidopsis thaliana",
                                      "Arabidopsis lyrata",
                                       "Capsella rubella"))
# look at file paths
file_paths

# download the proteomes of three different species at the same time
#### Database: ENSEMBL
file_paths <- getProteomeSet(db = "ensembl", organisms = c("Homo sapiens",
                                      "Mus musculus",
                                       "Caenorhabditis elegans"))
# look at file paths
file_paths

# download the proteomes of three different species at the same time
#### Database: UniProt
file_paths <- getProteomeSet(db = "uniprot", organisms = c("Homo sapiens",
                                      "Mus musculus",
                                       "Caenorhabditis elegans"))
# look at file paths
file_paths

## End(Not run)

Description

Retrieve available database releases or versions of ENSEMBL.

Usage

getReleases(db = "ensembl")

Arguments

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
# retrieve available resease versions of ENSEMBL
getReleases("ensembl")

## End(Not run)

Description

Main Repeat Masker output retrieval function for an organism of interest. By specifying the scientific name of an organism of interest the corresponding Repeat Masker file storing the genome of the organism of interest can be downloaded and stored locally. Repeat Masker files can be retrieved from several databases.

Usage

getRepeatMasker(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  gunzip = FALSE,
  path = file.path("_ncbi_downloads", "repeatmasker"),
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory '_ncbi_downloads/repeatmasker' to store the files of interest as fasta file for future processing. In case the corresponding fasta file already exists within the '_ncbi_downloads/repeatmasker' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded Repeat Masker output file.

Author(s)

Hajk-Georg Drost

See Also

getGenome, getProteome, getCDS, getGFF, getRNA, getCollection, meta.retrieval, read_rm

Examples

## Not run: 

# download the Repeat Masker output file of Homo sapiens from refseq
# and store the corresponding genome file in '_ncbi_downloads/genomes'
file_path <- getRepeatMasker( db       = "refseq",
             organism = "Homo sapiens",
             path = file.path("_ncbi_downloads","repeatmasker"))

Hsap_repeatmasker <- read_rm(file_path)


## End(Not run)

Description

Main retrieval function for RNA sequences of an organism of interest. By specifying the scientific name of an organism of interest the corresponding fasta-file storing the RNA information for the organism of interest can be downloaded and stored locally. RNA files can be retrieved from several databases.

Usage

getRNA(
  db = "refseq",
  organism,
  reference = FALSE,
  skip_bacteria = TRUE,
  release = NULL,
  assembly_type = "toplevel",
  path = file.path("_ncbi_downloads", "RNA"),
  gunzip = FALSE,
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory relative to file type, if you get fasta genomes it will be _ncbi_downloads/genomes'. In case the corresponding fasta file already exists within the '_ncbi_downloads/genomes' folder and is accessible within the workspace, no download process will be performed. For other file types the same rule applies.

Value

File path to downloaded genome.

Author(s)

Hajk-Georg Drost

See Also

Other getBio: getBio(), getCDS(), getCollection(), getGFF(), getGenome(), getProteome()

Other rna: getRNASet(), read_rna()

Examples

## Not run: 
# download the RNA of Arabidopsis thaliana from refseq
# and store the corresponding RNA file in '_ncbi_downloads/RNA'
file_path <- getRNA( db       = "refseq",
             organism = "Arabidopsis thaliana",
             path     = file.path("_ncbi_downloads","RNA"))

Ath_RNA <- read_rna(file_path, format = "fasta")

## End(Not run)

Description

Main RNA retrieval function for a set of organism of interest. By specifying the scientific names of the organisms of interest the corresponding fasta-files storing the RNA of the organisms of interest will be downloaded and stored locally. RNA files can be retrieved from several databases.

Usage

getRNASet(
  db = "refseq",
  organisms,
  reference = FALSE,
  release = NULL,
  skip_bacteria = TRUE,
  gunzip = TRUE,
  update = FALSE,
  path = "set_RNAs",
  mute_citation = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI:

refseq: ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/

genbank: ftp://ftp.ncbi.nlm.nih.gov/genomes/genbank/

and creates a directory 'set_CDSs' to store the CDSs of interest as fasta files for future processing. In case the corresponding fasta file already exists within the 'set_CDSs' folder and is accessible within the workspace, no download process will be performed.

Value

File path to downloaded genomes (names are identifiers: 'new' (file was downloaded now), 'old' files did already exist)

Author(s)

Hajk-Georg Drost

See Also

Other getBioSet: getBioSet(), getCDSSet(), getCollectionSet(), getGFFSet(), getGenomeSet(), getProteomeSet()

Other rna: getRNA(), read_rna()

Examples

## Not run: 
getBioSet("refseq", organisms = c("Arabidopsis thaliana",
                                  "Arabidopsis lyrata",
                                  "Capsella rubella"),
                                  set_type = "cds")

## End(Not run)

Description

Retrieval function of the assembly_summary.txt file from NCBI.

Usage

getSummaryFile(db, kingdom, file = assemblies_info_path(db, kingdom))

Arguments

Author(s)

Hajk-Georg Drost

See Also

getKingdomAssemblySummary, getMetaGenomeSummary

Examples

## Not run: 
test <- getSummaryFile("refseq","plant")
test

## End(Not run)

Description

Get uniprot info from organism

Usage

getUniProtInfo(organism, path = cachedir(), update = TRUE)

Arguments

Description

The UniProt stores a STATS file to summarise all available information for their reference proteomes. Users can now download this file and process it with biomartr.

Usage

getUniProtSTATS(update = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
# retrieve STATS file from UniProt
uniprot_info <- getUniProtSTATS(update = TRUE)
# look at results
uniprot_info

## End(Not run)

Description

This function checks the availability of a given genome on the NBCI servers specified as scientific name.

Usage

is.genome.available(
  db = "refseq",
  organism,
  skip_bacteria = TRUE,
  details = FALSE
)

Arguments

Details

Internally this function calls the listGenomes function to detect all available genomes and checks whether or not the specified organism is available for download.

Value

a logical value specifing whether or not the genome of the input organism is available. In case details = TRUE only a character string specifying the genome details is being returned.

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
# checking whether the Homo sapiens genome is stored on NCBI
is.genome.available(organism = "Homo sapiens", db = "refseq")

# and printing details
is.genome.available(organism = "Homo sapiens", db = "refseq", details = TRUE)

# checking whether the Homo sapiens genome is stored on ENSEMBL
is.genome.available(organism = "Homo sapiens", db = "ensembl")

# and printing details
is.genome.available(organism = "Homo sapiens",
                    details = TRUE,
                    db = "ensembl")

## End(Not run)

Description

This function allows you to retrieve a list of database names and versions that can be downloaded from correspondning servers.

Database retrieval is crucial for most biological studies and analyses. There is a vast diversity of databases that can be accessed remotely or that can be downloaded to your local machine. This function provides an interface to databases that can be downloaded from NCBI servers and lists all available databases and their database version to be able to select an appropriate database for download with download.database.

Usage

listDatabases(db = "nr", update = FALSE)

listNCBIDatabases(db = "nr", update = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

download.database, download.database.all

Examples

## Not run: 
# retrieve all versions of the NCBI 'nr' database that can be downloaded
listNCBIDatabases(db = "nr")

# analogous:
# listNCBIDatabases(db = "cdd")
# listNCBIDatabases(db = "nt")
# listNCBIDatabases(db = "gss")
# listNCBIDatabases(db = "refseq_protein")

## End(Not run)

Description

This function retrieves the names of all genomes available on the NCBI ftp:// server and stores the results in a file named 'overview.txt' inside the directory _ncbi_downloads' that is built inside the workspace.

Usage

listGenomes(
  db = "refseq",
  type = "all",
  subset = NULL,
  details = FALSE,
  update = FALSE,
  skip_bacteria = FALSE
)

Arguments

Details

Internally this function loads the the overview.txt file from NCBI and creates a directory '_ncbi_downloads' in the temdir() folder to store the overview.txt file for future processing. In case the overview.txt file already exists within the '_ncbi_downloads' folder and is accessible within the workspace, no download process will be performed again.

Note

Please note that the ftp:// connection relies on the NCBI or ENSEMBL server and cannot be accurately accessed via a proxy.

Author(s)

Hajk-Georg Drost

Examples

## Not run: 
# print details for refseq
listGenomes(db = "refseq")
# print details for all plants in refseq
listGenomes(db = "refseq", type = "kingdom")
# print details for all plant groups in refseq
listGenomes(db = "refseq", type = "group")
# print details for all plant subgroups in refseq
listGenomes(db = "refseq", type = "subgroup")
# Ensembl
listGenomes(db = "ensembl", type = "kingdom", subset = "EnsemblVertebrates")

## End(Not run)

Description

Users can retrieve the available number of sequenced genomes per group. Only available for db = "refseq" and db = "genbank".

Usage

listGroups(db = "refseq", kingdom = "all", details = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

listGenomes, is.genome.available, listKingdoms

Examples

## Not run: 
# example for refseq
listGroups(db = "refseq")
# example for genbank
listGroups(db = "genbank")
### in case groups should be specified by kingdom
# first, retrieve available kingdom names
listKingdoms()
# now we choose kingdom "bacteria"
listGroups(db = "refseq", kingdom = "bacteria")
# or
listGroups(db = "genbank", kingdom = "bacteria")

## End(Not run)

Description

Users can retrieve the available number of sequenced genomes per kingdom.

Usage

listKingdoms(db = "refseq")

Arguments

Author(s)

Hajk-Georg Drost

See Also

listGenomes, is.genome.available, listGroups

Examples

## Not run: 
# list number of available genomes in refseq for each kingdom of life
listKingdoms(db = "refseq")
# example for genbank
listKingdoms(db = "genbank")
# example for ensembl
listKingdoms(db = "ensembl")

## End(Not run)

Description

List available metagenomes on NCBI genbank. NCBI genbank allows users to download entire metagenomes of several metagenome projects. This function lists all available metagenomes that can then be downloaded via getMetaGenomes.

Usage

listMetaGenomes(details = FALSE)

Arguments

Author(s)

Hajk-Georg Drost

See Also

getMetaGenomes, getMetaGenomeSummary

Examples

## Not run: 
# retrieve available metagenome projects at NCBI Genbank
listMetaGenomes()
# retrieve detailed information on available metagenome projects 
# at NCBI Genbank
listMetaGenomes(details = TRUE)

## End(Not run)

Description

Download genomes, proteomes, cds, gff, rna, or assembly stats files of all species within a kingdom of life.

Usage

meta.retrieval(
  db = "refseq",
  kingdom,
  group = NULL,
  type = "genome",
  restart_at_last = TRUE,
  reference = FALSE,
  combine = FALSE,
  path = NULL
)

Arguments

Details

This function aims to perform bulk retrieval of the genomes, proteomes, cds, etc. of species that belong to the same kingdom of life or to the same subgroup.

Value

a character vector storing the file paths of the retrieved files.

Author(s)

Hajk-Georg Drost

See Also

Other meta_retrival: meta.retrieval.all()

Examples

## Not run: 
# get all available kingdoms for refseq
getKingdoms(db = "refseq")
# download all vertebrate genomes from refseq
meta.retrieval(kingdom = "vertebrate_mammalian",
               db = "refseq",
               type = "genome")

# get all available kingdoms for genbank
getKingdoms(db = "genbank")
# download all vertebrate genomes from genbank
meta.retrieval(kingdom = "vertebrate_mammalian",
               db = "genbank",
               type = "genome")


# In case users do not wish to retrieve genomes from an entire kingdom,
# but rather from a subgoup (e.g. from species belonging to the
# Gammaproteobacteria class, a subgroup of the bacteria kingdom),
# they can use the following workflow"
# First, users can again consult the getKingdoms() function to retrieve
# kingdom information.
getKingdoms(db = "refseq")

# In this example, we will choose the bacteria kingdom.
# Now, the getGroups() function allows users to obtain available
# subgroups of the bacteria kingdom.
getGroups(db = "refseq", kingdom = "bacteria")

# Now we choose the group Gammaproteobacteria and specify
# the group argument in the meta.retrieval() function
meta.retrieval(kingdom = "bacteria",
   roup = "Gammaproteobacteria",
   db = "refseq",
   type = "genome")

## End(Not run)

Description

Download genomes, proteomes, cds, gff, rna, or assembly stats files of individual species of all kingdoms of life.

Usage

meta.retrieval.all(db = "refseq", type = "genome", reference = FALSE)

Arguments

Details

This function aims to perform bulk retrieval of all genomes of species for all kingdoms of life.

Value

a character vector storing the file paths of the retrieved files.

Author(s)

Hajk-Georg Drost

See Also

Other meta_retrival: meta.retrieval()

Examples

## Not run: 
# download all genomes from refseq
meta.retrieval.all(db = "refseq", type = "genome")
# download all vertebrate genomes from genbank
meta.retrieval.all(db = "genbank", type = "genome")
# download all vertebrate genomes from ensemblgenomes
meta.retrieval.all(db = "genbank", type = "ensemblgenomes")

## End(Not run)

Description

In addition to the organismBM function, this function returns all available attributes that can be accessed through different marts and datasets for a given query organism.

Usage

organismAttributes(organism, update = FALSE, topic = NULL)

Arguments

Details

For a given query organism, this function retrieves all available attributes that can be accessed through different marts and datasets.

Sometimes the same attribute names correspond to different datasets and marts causing problems when using getMarts. The approach introduced by this function provides (again) a organism centric way of accessing organism specific attributes.

The topic argument allows the user to search for specific attribute topics/categories for faster filtering.

Value

a data.frame storing corresponding attribute names, description, datasets, and marts.

Note

When you run this function for the first time, the data retrieval procedure will take some time, due to the remote access to BioMart. The corresponding result is then saved in a *.txt file within the tempdir directory named "_biomart/listMarts.txt","_biomart/listDatasets.txt", and "_biomart/listAttributes_organism.txt", allowing subsequent queries to perform much faster.

Author(s)

Hajk-Georg Drost

References

http://biomart.org/

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Steffen Durinck, Paul T. Spellman, Ewan Birney and Wolfgang Huber, Nature Protocols 4, 1184-1191 (2009).

BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Steffen Durinck, Yves Moreau, Arek Kasprzyk, Sean Davis, Bart De Moor, Alvis Brazma and Wolfgang Huber, Bioinformatics 21, 3439-3440 (2005).

See Also

organismFilters, organismBM, biomart, listAttributes

Examples

## Not run:  
# search for attribute topic id
head(organismAttributes("Homo sapiens", topic = "id"), 20)

## End(Not run)

Description

This function returns either all available biomart connections for all available organisms for which biomart access is possible, or (when specified) returns all organism specific biomart connections.

Usage

organismBM(organism = NULL, update = FALSE, mute_citation = TRUE)

Arguments

Details

This function collects all available biomart connections and returns a table storing the organism for which biomart connections are available as well as the corresponding mart and database.

Note

When you run this function for the first time, the data retrieval procedure will take some time, due to the remote access to BioMart. The corresponding result is then saved in a *.txt file named "_biomart/listDatasets.txt" in the tempdir directory, allowing subsequent queries to perform much faster.

Author(s)

Hajk-Georg Drost

References

http://biomart.org/

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Steffen Durinck, Paul T. Spellman, Ewan Birney and Wolfgang Huber, Nature Protocols 4, 1184-1191 (2009).

BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Steffen Durinck, Yves Moreau, Arek Kasprzyk, Sean Davis, Bart De Moor, Alvis Brazma and Wolfgang Huber, Bioinformatics 21, 3439-3440 (2005).

See Also

Other biomaRt: biomart(), getAttributes(), getDatasets(), getMarts(), organismFilters()

Examples

## Not run: 
# returning all available biomart connections
head(organismBM(), 20)
# retrieving all available datasets and biomart connections for
# a specific query organism (scientific name)
organismBM(organism = "Homo sapiens")
# you can also update the downloaded version using
# the "update = TRUE" argument
head(organismBM(update = TRUE), 20)

## End(Not run)

Description

In addition to the organismBM and organismAttributes functions, this function returns all available filters that can be accessed through different marts and datasets for a given query organism.

Usage

organismFilters(organism, update = FALSE, topic = NULL)

Arguments

Details

For a given query organism, this function retrieves all available filters that can be accessed through different marts and datasets.

Sometimes the same filter names correspond to different datasets and marts causing problems when using getMarts. The approach introduced by this function provides (again) a organism centric way of accessing organism specific filters.

The topic argument allows the user to search for specific filters topics/categories for faster selection.

Value

a data.frame storing corresponding filter names, description, datasets, and marts.

Note

When you run this function for the first time, the data retrieval procedure will take some time, due to the remote access to BioMart. The corresponding result is then saved in a *.txt file within the tempdir directory named "_biomart/listMarts.txt","_biomart/listDatasets.txt", and "_biomart/listFilters_organism.txt", allowing subsequent queries to perform much faster.

Author(s)

Hajk-Georg Drost

References

http://biomart.org/

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Steffen Durinck, Paul T. Spellman, Ewan Birney and Wolfgang Huber, Nature Protocols 4, 1184-1191 (2009).

BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Steffen Durinck, Yves Moreau, Arek Kasprzyk, Sean Davis, Bart De Moor, Alvis Brazma and Wolfgang Huber, Bioinformatics 21, 3439-3440 (2005).

See Also

Other biomaRt: biomart(), getAttributes(), getDatasets(), getMarts(), organismBM()

Examples

## Not run: 
# search for filter topic "id"
head(organismFilters("Homo sapiens", topic = "id"), 20)

## End(Not run)

Description

This function reads an organism specific Genome Assembly Stats file that was retrieved with getAssemblyStats.

Usage

read_assemblystats(file, type = "raw")

Arguments

Details

This function takes a string specifying the path to the Genome Assembly Stats file of interest (e.g. the path returned by getAssemblyStats) and imports it.

Author(s)

Hajk-Georg Drost

See Also

getAssemblyStats, read_genome, read_proteome, read_cds, read_gff

Description

This function reads an organism specific CDS stored in a defined file format.

Usage

read_cds(
  file,
  format = "fasta",
  obj.type = "Biostrings",
  delete_corrupt = FALSE,
  ...
)

Arguments

Details

The read.cds function takes a string specifying the path to the cds file of interest as first argument.

It is possible to read in different proteome file standards such as fasta or genebank.

CDS stored in fasta files can be downloaded from http://www.ensembl.org/info/data/ftp/index.html.

Value

A data.table storing the gene id in the first column and the corresponding sequence as string in the second column.

Author(s)

Hajk-Georg Drost

See Also

Other cds: getCDS(), getCDSSet()

Other readers: read_genome(), read_gff(), read_proteome(), read_rna()

Description

This function reads an organism specific genome stored in a defined file format.

Usage

read_genome(file, format = "fasta", obj.type = "Biostrings", ...)

Arguments

Details

This function takes a string specifying the path to the genome file of interest as first argument (e.g. the path returned by getGenome).

Value

Either a Biostrings or data.table object.

Author(s)

Hajk-Georg Drost

See Also

Other genome: getGenome(), getGenomeSet()

Other readers: read_cds(), read_gff(), read_proteome(), read_rna()

Description

This function reads an organism specific CDS stored in a defined file format.

Usage

read_gff(file)

Arguments

Details

This function takes a string specifying the path to the GFF file of interest (e.g. the path returned by getGFF).

Value

Either a Biostrings or data.table object.

Author(s)

Hajk-Georg Drost

See Also

Other gff: getGFF(), getGFFSet()

Other readers: read_cds(), read_genome(), read_proteome(), read_rna()

Description

This function reads an organism specific proteome stored in a defined file format.

Usage

read_proteome(file, format = "fasta", obj.type = "Biostrings", ...)

Arguments

Details

This function takes a string specifying the path to the proteome file of interest as first argument.

It is possible to read in different proteome file standards such as fasta or genebank.

Value

Either a Biostrings or data.table object.

Author(s)

Hajk-Georg Drost

See Also

Other readers: read_cds(), read_genome(), read_gff(), read_rna()

Other proteome: getProteome(), getProteomeSet()

Description

This function reads an organism specific Repeat Masker output file.

Usage

read_rm(file)

Arguments

Details

This function takes a string specifying the path to the Repeat Masker output file of interest as first argument.

Author(s)

Hajk-Georg Drost

See Also

getRepeatMasker, read_genome, read_proteome, read_gff, read_rna

Description

This function reads an organism specific RNA stored in a defined file format.

Usage

read_rna(file, format = "fasta", obj.type = "Biostrings", ...)

Arguments

Details

This function takes a string specifying the path to the RNA file of interest as first argument. It is possible to read in different proteome file standards such as fasta or genebank.

Value

A data.table storing the gene id in the first column and the corresponding sequence as string in the second column.

Author(s)

Hajk-Georg Drost

See Also

Other rna: getRNA(), getRNASet()

Other readers: read_cds(), read_genome(), read_gff(), read_proteome()

Description

This function extracts all organism names (scientific names) for which genomes, proteomes, and CDS files are stored on the NCBI refseq server.

Usage

refseqOrganisms()

Author(s)

Hajk-Georg Drost

Description

A summary statistics of specific CDS features is returned.

Usage

summary_cds(file, organism)

Arguments

Details

The summary statistics include:

• total_seqs:

• nnn_abs: The total number of NNN's (over all chromosomes/scaffolds/contigs) in all coding sequences combined

• nnn_perc: The percentage (relative frequency) of NNN's (over all chromosomes/scaffolds/contigs) compared to the total number of nucleotides of all coding sequences

Author(s)

Hajk-Georg Drost

See Also

getCollection, getCDS, read_cds, summary_genome

Description

A summary statistics of specific genome features is generated. These statistics are useful to assess the genome quality of retrieved genome assemblies when performing comparative genomics tasks. This way, users can assess whether or not patterns found based on genome comparisons aren't just a technical artifact of differences in genome assembly quality.

Usage

summary_genome(file, organism)

Arguments

Details

The summary statistics include:

• genome_size_mbp: Genome size in mega base pairs

• n50_mbp: The N50 contig size of the genome assembly in mega base pairs

• n_seqs: The number of chromosomes/scaffolds/contigs of the genome assembly file

• n_nnn: The absolute number of NNNs (over all chromosomes or scaffolds or contigs) in the genome assembly file

• rel_nnn: The percentage (relative frequency) of NNNs (over all chromosomes or scaffolds or contigs) compared to the total number of nucleotides in the genome assembly file

• genome_entropy: The Shannon Entropy of the genome assembly file (median entropy over all individual chromosome entropies)

• n_gc: The total number of GCs (over all chromosomes or scaffolds or contigs) in the genome assembly file

• rel_gc: The (relative frequency) of GCs (over all chromosomes or scaffolds or contigs) compared to the total number of nucleotides in the genome assembly file

Author(s)

Hajk-Georg Drost

See Also

summary_cds, getCollection, getGenome, read_genome

Examples

## Not run: 
# retrieve genome from NCBI RefSeq
Sc <- biomartr::getGenome(db = "refseq", organism = "Saccharomyces cerevisiae")
# compute genome assembly summary statistics
Sc_genome_summary <- summary_genome(file = Sc, organism = "Saccharomyces cerevisiae")
# look at results
Sc_genome_summary

## End(Not run)