R/vectorizeORFs.R

In rfctbio-bsu/ORFhunteR: Predict open reading frames in nucleotide sequences

#' Vectorize the ORF(-s) sequence(-s) to sequence features
#' @description Vectorize the ORF(-s) sequence(-s) to sequence features.
#' @param x DNAStringSet object with ORF(-s) sequence(-s).
#' @return The object of class data.frame
#'     with ORF(-s) vectorized into sequence features.
#' @author Mikalai M. Yatskou
#' @examples
#' x = DNAStringSet(x = "ATGGGCCTCA")
#' feats <- vectorizeORFs(x = x)
#' @export

vectorizeORFs = function(x){
  ### A vector of dinucleotides for calculation of correlation factors.
  diNucls = c("AT", "AG", "AC", "TG", "TC", "GC")
  ### Calculation of correlation factors.
  corFcs <- lapply(X=diNucls,
                   FUN=function(y){do.call(what=c,
                                          args=sapply(X=as.character(x),
                                                      FUN=getCorrelationFactors,
                                                      pattern=y,
                                                      blockSize=10,
                                                      simplify=FALSE,
                                                      USE.NAMES=FALSE))})
  corFcs <- data.frame(do.call(what=cbind, args=corFcs))
  ### Calculation of Bao metrics.
  bao <- do.call(what=rbind, args=sapply(X=as.character(x),
                                         FUN=getBaoMetrics,
                                         indexes=length(x=x),
                                         types=length(x=x),
                                         simplify=FALSE,
                                         USE.NAMES=FALSE))[, -1:-2]
  ### Calculation of oligonucleotides frequency (1-mer to 3-mer).
  mo <- data.frame(oligonucleotideFrequency(x=x, width=1, as.prob=TRUE))
  di <- data.frame(oligonucleotideFrequency(x=x, width=2, as.prob=TRUE))
  tr <- data.frame(oligonucleotideFrequency(x=x, width=3, as.prob=TRUE))
  ### Consolidation of all ORF features in a single object of class data.frame.
  features <- cbind(mo, di, tr, corFcs, nchar(x=x), log10(x=nchar(x=x)), bao)
  rownames(x=features) <- NULL
  colnames(x=features) <- c(paste("freq", colnames(x=features)[1:84], sep=""),
                            paste("corrFact", diNucls, sep=""),
                            "length", "logLength",
                            colnames(x=features)[93:104])
  ### Returning finnal results.
  return(features)
}