R/get_negativePPI.R

In mrbakhsh/HPiP: Host-Pathogen Interaction Prediction

    #' get_negativePPI
    #' @title Construct Negative Reference Host-Pathogen
    #' Protein-Protein Interactions (HP-PPIs)
    #' @param prot1 A character vector containing pathogen proteins.
    #' @param prot2 A character vector containing host proteins.
    #' @param TPset A character vector containing positive reference
    #' interactions.
    #' @return A Data.frame containing true negative interactions.
    #' @author Matineh Rahmatbakhsh, \email{matinerb.94@gmail.com}
    #' @references Eid, F.-E., ElHefnawi, M., and Heath, L. S. (2016).
    #' DeNovo: virus-host sequence-based protein–protein interaction
    #' prediction. Bioinformatics 32, 1144–1150.
    #' @seealso See \code{\link{get_positivePPI}} for generating positive
    #' protein-protein interaction.
    #' @description Construct true negative protein-protein interactions
    #' from the positive interactions. In the context of PPI prediction,
    #' a negative interaction is a pair of proteins that unlikely to interact.
    #' Since there is no experimentally verified
    #' non-interacting pair, the negative sampling can be used to construct the
    #' negative reference set. The negative sampling can be constructed from a
    #' set of host proteins, a set of pathogen proteins, and a list of positive
    #' reference interactions between members of host and pathogen proteins
    #' (Eid et al., 2016).
    #' @export
    #' @examples
    #' prot1 <- c("P0DTC4", "P0DTC5", "P0DTC9")
    #' prot2 <- c("Q9Y679", "Q9NW15", "Q9NXF8")
    #' TPset <- c("P0DTC4~P31948", "P0DTC8~Q13438")
    #' TN_PPI <- get_negativePPI(prot1, prot2, TPset)
    #' head(TN_PPI)
    get_negativePPI <-
      function(prot1, prot2, TPset) {
        if (!is.character(prot1)) {
          stop("prot1 must be a character vector")
        }

        if (!is.character(prot2)) {
          stop("prot2 must be a character vector")
        }

        if (!is.character(TPset)) {
          stop("TPset must be a character vector")
        }

        TN_PPI <-
          apply(expand.grid(prot1, prot2), 1, paste, collapse = "~")

        PPI <- setdiff(TN_PPI, TPset)
        TN_PPI <- as.data.frame(PPI)


        return(TN_PPI)
      }