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#' 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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