getGFF {biomartr}

Genome Annotation Retrieval (GFF3)

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

db

a character string specifying the database from which the genome shall be retrieved:

• db = "refseq"

• db = "genbank"

• db = "ensembl"

organism

Organism selector id, there are three options to characterize an organism:

• by scientific name: e.g. organism = "Homo sapiens"

• by database specific accession identifier: e.g. organism = "GCF_000001405.37" (= NCBI RefSeq identifier for Homo sapiens)

• by taxonomic identifier from NCBI Taxonomy: e.g. organism = "9606" (= taxid of Homo sapiens)

reference

a logical value indicating whether or not a genome shall be downloaded if it isn't marked in the database as either a reference genome or a representative genome.

skip_bacteria

Due to its enormous dataset size (> 700MB as of July 2023), the bacterial summary file will not be loaded by default anymore. If users wish to gain insights for the bacterial kingdom they needs to actively specify skip_bacteria = FALSE. When skip_bacteria = FALSE is set then the bacterial summary file will be downloaded.

release

a numeric, the database release version of ENSEMBL (db = "ensembl"). Default is release = NULL meaning that the most recent database version is used. release = 75 would for human would give the stable GRCh37 release in ensembl. Value must be > 46, since ensembl did not structure their data if the standard format before that.

gunzip

a logical, indicating whether or not files should be unzipped.

remove_annotation_outliers

shall outlier lines be removed from the input annotation_file? If yes, then the initial annotation_file will be overwritten and the removed outlier lines will be stored at tempdir for further exploration.

path

a character string specifying the location (a folder) in which the corresponding annotation file shall be stored. Default is path = file.path("_ncbi_downloads","annotation").

mute_citation

logical, default FALSE, indicating whether citation message should be muted.

format

"gff3", alternative "gtf" for ensembl.

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)