R/get_features.R

In drawProteins: Package to Draw Protein Schematics from Uniprot API output

#' GET features of protein(s) from UniProt API
#'
#' This function creates the URL required to query the UniProt API and returns
#' the features of the protein or proteins in JSON format. It uses the GET()
#' function from the httr package.
#'
#' @param proteins_acc A vector of length 1 with one or more UniProt accession
#' numbers separated by spaces.
#'
#' @return If there is internet access and the UniProt accession numbers are
#' good, the function will return a list of lists. The list will be of length
#' equivalent to the number of Uniprot accession numbers supplied. The lists
#' inside will be of length 6 and will contain information about the proteins
#' and the features.
#'
#' @examples
#' # Requires internet access
#' prot_data <- get_features("Q04206 Q01201 Q04864 P19838 Q00653")
#'
#' @import httr
#'
#' @export
# get_features function to GET protein data from Uniprot
get_features <- function(proteins_acc){

    # accession numbers need to be combined with "%2C" for Uniprot API
    proteins_acc_url <- gsub(" ", "%2C", proteins_acc)

    # this is the baseurl for a multiple features query
    baseurl<-
"https://www.ebi.ac.uk/proteins/api/features?offset=0&size=100&accession="

    # make url to GET features for multiple accession numbers
    url <- paste0(baseurl, proteins_acc_url)

    # basic function is GET() which accesses the API
    # accept_json() argument gives a JSON object
    prots_feat <- httr::GET(url, httr::accept_json())

    code <- httr::status_code(prots_feat)  # if it returns a 200 - that's good
    if(code == 200){
        print("Download has worked")
    } else {print(paste("An error has occured. Code:", code))}

# extract content() - gives a list with length = number of acc no
    prots_feat_red <- httr::content(prots_feat)
    return(prots_feat_red)
}


### error handling required:
# no internet connection
# one or more accession numbers not in uniprot - warning

### enhanced functionality for future:
# R object with accession numbers
# other separation options
# import file (csv, tsv, excel)
# import from other Bioconductor packages
# formats other than accession numbers?
# - other databases...