Proteome retrieval of multiple species — getProteomeSet • biomartr
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.

# Proteome retrieval of multiple species

Source: `R/getSet.R`
`getProteomeSet.Rd`

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.

    getProteomeSet(
      db = "refseq",
      organisms,
      reference = FALSE,
      release = NULL,
      skip_bacteria = TRUE,
      gunzip = TRUE,
      update = FALSE,
      path = "set_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"`

organisms

  a character vector storing the names of the organisms than shall be retrieved. There are three available options to characterize an organism:

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.

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.

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.

gunzip

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

update

  logical, default FALSE. Updated backend cached files needed. Usually keep this false, to make ut run much faster. Only set to TRUE, if you believe you cache is outdated (Species only exist in newest release etc)

path

  a character string specifying the location (a folder) in which the corresponding proteomes shall be stored. Default is `path` = `"set_proteomes"`.

mute_citation

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

## Value

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

## 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.

## See also

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

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

## Author

Hajk-Georg Drost

## Examples

    if (FALSE) {
    # 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
    }