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 forHomo sapiens
)by
taxonomic identifier from NCBI Taxonomy
: e.g.organism = "9606"
(= taxid ofHomo 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
. Whenskip_bacteria = FALSE
is set then the bacterial summary file will be downloaded.- release
a numeric, the database release version of ENSEMBL (
db = "ensembl"
). Default isrelease = 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 initialannotation_file
will be overwritten and the removed outlier lines will be stored attempdir
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
Fetching of assembly / sequence data is done by fetching an overview file
from metadata of given database:
For NCBI (refseq/genbank):
Internally this function loads the the overview.txt file from NCBI:
refseq: ftp.ncbi.nlm.nih.gov/genomes/refseq/
genbank: ftp.ncbi.nlm.nih.gov/genomes/genbank/
It will then create a directory relative to file type wanted,
if you get fasta genomes it will be
_ncbi_downloads/genomes' etc.
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.
For ensembl it fetches overview per type from the rest API:
ensembl: https://rest.ensembl.org
See also
Other getBio:
getBio()
,
getCDS()
,
getCollection()
,
getGenome()
,
getProteome()
,
getRNA()
Examples
if (FALSE) { # \dontrun{
# 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)
} # }