getProteome: Proteome Retrieval

View source: R/getProteome.R

getProteomeR Documentation

Proteome Retrieval

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

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.

update

logical, default TRUE. (Uniprot only for now!) If species info file exists already, do not re download, makes it faster but the file can be old, i.e. no longer as complete as it could be.

path

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

mute_citation

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

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)

HajkD/biomartr documentation built on Dec. 9, 2023, 7:25 p.m.