Proteome Retrieval — getProteome • biomartr
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.

# Proteome Retrieval

Source: `R/getProteome.R`
`getProteome.Rd`

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.

    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.

## Value

File path to downloaded proteome.

## 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.

## See also

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

Other proteome: `getProteomeSet()`, `read_proteome()`

## Author

Hajk-Georg Drost

## Examples

    if (FALSE) {
    # 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")
    }