R/desc-09-CTDD.R

#' CTD Descriptors - Distribution
#'
#' This function calculates the Distribution descriptor of the
#' CTD descriptors (dim: 105).
#'
#' @param x A character vector, as the input protein sequence.
#'
#' @return A length 105 named vector
#'
#' @author Nan Xiao <\url{https://nanx.me}>
#'
#' @seealso See \code{\link{extractCTDC}} and \code{\link{extractCTDT}}
#' for Composition and Transition of the CTD descriptors.
#'
#' @export extractCTDD
#'
#' @note For this descriptor type, users need to intelligently evaluate
#' the underlying details of the descriptors provided, instead of using
#' this function with their data blindly. It would be wise to use some
#' negative and positive control comparisons where relevant to help guide
#' interpretation of the results.
#'
#' @references
#' Inna Dubchak, Ilya Muchink, Stephen R. Holbrook and Sung-Hou Kim.
#' Prediction of protein folding class using global description of
#' amino acid sequence. \emph{Proceedings of the National Academy of Sciences}.
#' USA, 1995, 92, 8700-8704.
#'
#' Inna Dubchak, Ilya Muchink, Christopher Mayor, Igor Dralyuk and Sung-Hou Kim.
#' Recognition of a Protein Fold in the Context of the SCOP classification.
#' \emph{Proteins: Structure, Function and Genetics}, 1999, 35, 401-407.
#'
#' @examples
#' x <- readFASTA(system.file("protseq/P00750.fasta", package = "protr"))[[1]]
#' extractCTDD(x)
extractCTDD <- function(x) {
  if (protcheck(x) == FALSE) {
    stop("x has unrecognized amino acid type")
  }

  group1 <- list(
    "hydrophobicity" = c("R", "K", "E", "D", "Q", "N"),
    "normwaalsvolume" = c("G", "A", "S", "C", "T", "P", "D"),
    "polarity" = c("L", "I", "F", "W", "C", "M", "V", "Y"),
    "polarizability" = c("G", "A", "S", "D", "T"),
    "charge" = c("K", "R"),
    "secondarystruct" = c("E", "A", "L", "M", "Q", "K", "R", "H"),
    "solventaccess" = c("A", "L", "F", "C", "G", "I", "V", "W")
  )

  group2 <- list(
    "hydrophobicity" = c("G", "A", "S", "T", "P", "H", "Y"),
    "normwaalsvolume" = c("N", "V", "E", "Q", "I", "L"),
    "polarity" = c("P", "A", "T", "G", "S"),
    "polarizability" = c("C", "P", "N", "V", "E", "Q", "I", "L"),
    "charge" = c(
      "A", "N", "C", "Q", "G", "H", "I", "L",
      "M", "F", "P", "S", "T", "W", "Y", "V"
    ),
    "secondarystruct" = c("V", "I", "Y", "C", "W", "F", "T"),
    "solventaccess" = c("R", "K", "Q", "E", "N", "D")
  )

  group3 <- list(
    "hydrophobicity" = c("C", "L", "V", "I", "M", "F", "W"),
    "normwaalsvolume" = c("M", "H", "K", "F", "R", "Y", "W"),
    "polarity" = c("H", "Q", "R", "K", "N", "E", "D"),
    "polarizability" = c("K", "M", "H", "F", "R", "Y", "W"),
    "charge" = c("D", "E"),
    "secondarystruct" = c("G", "N", "P", "S", "D"),
    "solventaccess" = c("M", "S", "P", "T", "H", "Y")
  )

  xSplitted <- strsplit(x, split = "")[[1]]
  n <- nchar(x)

  G <- vector("list", 7)
  for (i in 1:7) G[[i]] <- rep(NA, n)

  # Get groups for each property & each amino acid

  for (i in 1:7) {
    try(G[[i]][which(xSplitted %in% group1[[i]])] <- "G1")
    try(G[[i]][which(xSplitted %in% group2[[i]])] <- "G2")
    try(G[[i]][which(xSplitted %in% group3[[i]])] <- "G3")
  }

  # Compute Distribution

  D <- vector("list", 7)
  for (i in 1:7) D[[i]] <- matrix(ncol = 5, nrow = 3)

  for (i in 1:7) {
    for (j in 1:3) {
      inds <- which(G[[i]] == paste0("G", j))
      quartiles <- floor(length(inds) * c(0.25, 0.5, 0.75))

      quartiles[which(quartiles <= 0)] <- 1

      D[[i]][j, ] <- if (length(inds) > 0) {
        (inds[c(1, quartiles, length(inds))]) * 100 / n
      } else {
        0
      }
    }
  }

  D <- do.call(rbind, D)
  D <- as.vector(t(D))

  names(D) <- paste(
    rep(paste("prop", 1:7, sep = ""), each = 15),
    rep(rep(c(".G1", ".G2", ".G3"), each = 5), times = 7),
    rep(paste(".residue", c("0", "25", "50", "75", "100"), sep = ""), times = 21),
    sep = ""
  )

  D
}

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protr documentation built on May 18, 2019, 9:02 a.m.