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#' Generic functions for class phyDat
#'
#' These functions help to manipulate alignments of class phyDat.
#'
#'
#' \code{allSitePattern} generates all possible site patterns and can be useful
#' in simulation studies. For further details see the vignette
#' AdvancedFeatures.
#'
#' The generic function \code{c} can be used to to combine sequences and
#' \code{unique} to get all unique sequences or unique haplotypes.
#'
#' \code{phyDat} stores identical columns of an alignment only once and keeps an
#' index of the original positions. This saves memory and especially
#' computations as these are usually need to be done only once for each site
#' pattern.
#' In the example below the matrix x in the example has 8 columns, but column 1
#' and 2 and also 3 and 5 are identical. The \code{phyDat} object y has only 6
#' site pattern. If argument \code{site.pattern=FALSE} the indexing behaves like
#' on the original matrix x. \code{site.pattern=TRUE} can be useful inside
#' functions.
#'
#' @aliases
#' cbind.phyDat c.phyDat removeUndeterminedSites
#' @param x An object containing sequences.
#' @param levels Level attributes.
#' @param n Number of sequences.
#' @param names Names of sequences.
#' @param subset a subset of taxa.
#' @param select a subset of characters.
#' @param site.pattern select site pattern or sites (see details).
#' @param incomparables for compatibility with unique.
#' @param identical if TRUE (default) sequences have to be identical, if FALSE
#' sequences are considered duplicates if distance between sequences is zero
#' (happens frequently with ambiguous sites).
#' @param type Type of sequences ("DNA", "AA" or "USER").
#' @param ... further arguments passed to or from other methods.
#' @return The functions return an object of class \code{phyDat}.
#' @author Klaus Schliep \email{klaus.schliep@@gmail.com}
#' @seealso \code{\link[ape]{DNAbin}}, \code{\link[ape]{as.DNAbin}},
#' \code{\link{baseFreq}}, \code{\link{glance.phyDat}}, \code{\link{dna2codon}},
#' \code{\link[ape]{read.dna}}, \code{\link[ape]{read.nexus.data}}
#' and the chapter 1 in the \code{vignette("AdvancedFeatures",
#' package="phangorn")} and the example of \code{\link{pmlMix}} for the use of
#' \code{\link{allSitePattern}}.
#' @keywords cluster
#' @examples
#'
#' data(Laurasiatherian)
#' class(Laurasiatherian)
#' Laurasiatherian
#' # base frequencies
#' baseFreq(Laurasiatherian)
#' # subsetting phyDat objects
#' # the first 5 sequences
#' subset(Laurasiatherian, subset=1:5)
#' # the first 5 characters
#' subset(Laurasiatherian, select=1:5, site.pattern = FALSE)
#' # subsetting with []
#' Laurasiatherian[1:5, 1:20]
#' # short for
#' subset(Laurasiatherian, subset=1:5, select=1:20, site.pattern = FALSE)
#' # the first 5 site patterns (often more than 5 characters)
#' subset(Laurasiatherian, select=1:5, site.pattern = TRUE)
#'
#' x <- matrix(c("a", "a", "c", "g", "c", "t", "a", "g",
#' "a", "a", "c", "g", "c", "t", "a", "g",
#' "a", "a", "c", "c", "c", "t", "t", "g"), nrow=3, byrow = TRUE,
#' dimnames = list(c("t1", "t2", "t3"), 1:8))
#' (y <- phyDat(x))
#'
#' subset(y, 1:2)
#' subset(y, 1:2, compress=TRUE)
#'
#' subset(y, select=1:3, site.pattern = FALSE) |> as.character()
#' subset(y, select=1:3, site.pattern = TRUE) |> as.character()
#' y[,1:3] # same as subset(y, select=1:3, site.pattern = FALSE)
#'
#' # Compute all possible site patterns
#' # for nucleotides there $4 ^ (number of tips)$ patterns
#' allSitePattern(5)
#'
#' @rdname phyDat
#' @export
print.phyDat <- function (x, ...){
cat(length(x), "sequences with",sum(attr(x,"weight")), "character and",
attr(x,"nr"),"different site patterns.\n")
cat("The states are",attr(x,"levels"), "\n")
}
#' @export cbind.phyDat
#' @export
cbind.phyDat <- function(..., gaps="-", compress=TRUE){
object <- as.list(substitute(list(...)))[-1]
x <- list(...)
n <- length(x)
if (n == 1) return(x[[1]])
types <- sapply(x, function(x)attr(x, "type"))
if(any(types!=types[1]))stop("Alignments must have same type!")
nr <- numeric(n)
ATTR <- attributes(x[[1]])
nr[1] <- sum(attr(x[[1]], "weight"))
allLevels <- attr(x[[1]], "allLevels")
gapsInd <- match(gaps, allLevels)
snames <- vector("list", n)
vec <- numeric(n+1)
wvec <- numeric(n+1)
objNames <- as.character(object)
if(any(duplicated(objNames))) objNames <- paste0(objNames, 1:n)
for(i in 1:n){
snames[[i]] <- names(x[[i]])
nr[i] <- sum(attr(x[[i]], "weight"))
vec[i+1] <- attr(x[[i]], "nr")
wvec[i+1] <- sum(attr(x[[i]], "weight"))
}
vec <- cumsum(vec)
wvec <- cumsum(wvec)
snames <- unique(unlist(snames))
weight <- numeric(vec[n+1])
index <- numeric(wvec[n+1])
ATTR$names <- snames
ATTR$nr <- vec[n+1]
tmp <- matrix(gapsInd, vec[n+1], length(snames),
dimnames = list(NULL, snames))
tmp <- as.data.frame(tmp)
add.index <- TRUE
for(i in 1:n){
nam <- names(x[[i]])
tmp[(vec[i]+1):vec[i+1], nam] <- x[[i]][nam]
weight[(vec[i]+1):vec[i+1]] <- attr(x[[i]], "weight")
}
if(compress){
dindex <- grp_duplicated(as.matrix(tmp), MARGIN=1)
attr(dindex, "nlevels") <- NULL
weight <- aggregate(weight, by=list(dindex), FUN=sum)$x
pos <- which(!duplicated(dindex))
tmp <- tmp[pos,]
}
if(any(sapply(x, function(x)is.null(attr(x, "index"))))) add.index <- FALSE
if(add.index & compress){
for(i in 1:n){
tmp2 <- attr(x[[i]], "index")
if(!is.null(tmp2)){
if(is.data.frame(tmp2))index[(wvec[i]+1):wvec[i+1]] <-
dindex[(vec[i]+1):vec[i+1]][tmp2[,1]]
else index[(wvec[i]+1):wvec[i+1]] <-
dindex[(vec[i]+1):vec[i+1]][tmp2]
}
else add.index <- FALSE
}
}
if(add.index) ATTR$index <- data.frame(index = index, genes=rep(objNames, nr))
ATTR$weight <- weight
ATTR$nr <- length(weight)
attributes(tmp) <- ATTR
tmp
}
# @rdname phyDat
#' @export c.phyDat
#' @export
rbind.phyDat <- function(...){
x <- list(...)
types <- sapply(x, function(x)attr(x, "type"))
l <- sapply(x, function(x)sum(attr(x, "weight")))
if(any(l!=l[1]))stop("Alignments have different # of characters!")
if(any(types!=types[1]))stop("Alignments must have same type!")
nam <- lapply(x, names) |> unlist()
if(any(duplicated(nam)))stop("Duplicated names!")
m <- lengths(x)
mcs <- c(0, cumsum(m))
res <- matrix(NA_character_, sum(m), l[1], dimnames=list(nam, NULL))
for(i in seq_along(x)){
res[(mcs[i]+1):mcs[i+1], ] <- as.character(x[[i]])
}
if(types[1]=="USER"){
contrast <- attr(x[[1]], "contrast")
dimnames(contrast) <- list(attr(x[[1]], "allLevels"),
attr(x[[1]], "levels"))
return(phyDat(res, type="USER", contrast=contrast))
}
phyDat(res, type=types[1])
}
# @rdname phyDat
#' @export c.phyDat
#' @export
c.phyDat <- cbind.phyDat
compress.phyDat <- function(data){
attrib <- attributes(data)
attr(data, "class") <- "list"
index <- grp_duplicated( matrix(unlist(data, use.names = FALSE), attrib$nr,
length(data)))
attrib$nr <- attr(index, "nlevels")
attr(index, "nlevels") <- NULL
pos <- which(!duplicated(index))
weight <- tapply(attrib$weight, index, sum)
names(weight) <- NULL
attrib$weight <- as.vector(weight)
if(is.null(attrib$index)) attrib$index <-index
else attrib$index <- index[attrib$index]
for(i in seq_len(length(data))) data[[i]] <- data[[i]][pos]
attributes(data) <- attrib
attr(data, "class") <- "phyDat"
data
}
uncompress.phyDat <- function(data){
attrib <- attributes(data)
stopifnot(all.equal(sum(attrib$weight), length(attrib$index)))
for(i in seq_along(data))
data[[i]] <- data[[i]][attrib$index]
attrib$nr <- length(attrib$index)
attrib$index <- seq_along(attrib$index)
attrib$weight <- rep(1, attrib$nr)
attributes(data) <- attrib
data
}
getCols <- function (data, cols, compress=FALSE){
attrib <- attributes(data)
if(inherits(attr(data, "index"), "data.frame")) compress <- FALSE
attr(data, "class") <- "list"
data <- data[cols]
if (is.character(cols))
attrib$names <- cols
else attrib$names <- attrib$names[cols]
attributes(data) <- attrib
attr(data, "class") <- "phyDat"
if(compress) return(compress.phyDat(data))
data
}
getRows <- function (data, rows, site.pattern = TRUE){
index <- attr(data, "index")
if(is.data.frame(index))index <- index[,1]
if(!site.pattern){
if(is.null(index)) index <- seq_len(length(data[[1]]))
weight <- tabulate(index[rows])
ind <- which(weight>0)
# update index
new_index <- integer(length(weight))
new_index[ind] <- seq_along(ind)
attr(data, "index") <- new_index[index[rows]]
rows <- ind # rows[ind]
weight <- weight[ind]
}
for (i in seq_along(data)){
if(is.matrix(data[[i]]))data[[i]] <- data[[i]][rows, ]
else data[[i]] <- data[[i]][rows]
}
attr(data, "weight") <- attr(data, "weight")[rows]
if(!site.pattern) attr(data, "weight") <- weight
attr(data, "nr") <- length(attr(data, "weight"))
if(site.pattern)attr(data, "index") <- NULL
data
}
#' @rdname phyDat
#' @method subset phyDat
#' @export
subset.phyDat <- function (x, subset, select, site.pattern = TRUE, ...){
if (!missing(subset)){
if(is.numeric(subset) & any(subset>length(x)))
stop("subscript out of bounds")
x <- getCols(x, subset, ...)
}
if (!missing(select)){
w <- attr(x, "weight")
if(site.pattern){
if(any(select > length(w))) stop("subscript out of bounds")
}
else if(any(select > sum(w))) stop("subscript out of bounds")
if(any(is.na(select))) return(NULL)
x <- getRows(x, select, site.pattern=site.pattern)
}
x
}
#' @param i,j indices of the rows and/or columns to select or to drop. They
#' may be numeric, logical, or character (in the same way than for standard R
#' objects).
#' @param drop for compatibility with the generic (unused).
#' @rdname phyDat
#' @export
"[.phyDat" <- function(x, i, j, ..., drop=FALSE){
subset(x, subset = i, select = j, site.pattern=FALSE, compress=FALSE)
}
#' @rdname phangorn-internal
#' @export
map_duplicates <- function(x, dist=length(x)<500, ...){
labels <- names(x)
nr <- attr(x, "nr")
if(dist){
y <- as.matrix(dist.hamming(x, FALSE))
l <- nrow(y)
ind <- duplicated(y)
}
else ind <- duplicated(x)
res <- NULL
if(any(ind)){
ind2 <- grp_duplicated( matrix(unlist(x, recursive = FALSE,
use.names = FALSE), nr, length(labels)), MARGIN=2)
if(dist) ind2 <- grp_duplicated(y)
ind2 <- ind2[ind]
res <- data.frame(duplicates=labels[ind], where=labels[!ind][ind2],
stringsAsFactors = FALSE)
}
res
}
#' @rdname phyDat
#' @method unique phyDat
#' @export
unique.phyDat <- function(x, incomparables=FALSE, identical=TRUE, ...){
tmp <- map_duplicates(x, !identical)
if (!is.null(tmp)) {
x <- getCols(x, setdiff(names(x), tmp[, 1]))
attr(x, "duplicated") <- list(tmp)
}
x
}
addTaxa <- function(tree, dup_list) {
fun <- function(x, dup_list){
if(Ntip(x)==1L){
dup <- dup_list[[1]][,1]
x <- add.tips(x, dup, rep(2, length(dup)))
dup_list[[1]] <- NULL
}
for (i in seq_along(dup_list)) {
dup <- dup_list[[i]]
x <- add.tips(x, dup[, 1], dup[, 2])
}
x
}
if(inherits(tree, "phylo")) return(fun(tree, dup_list))
if(inherits(tree, "multiPhylo")){
trees <- .uncompressTipLabel(tree)
trees <- unclass(trees)
trees <- lapply(trees, fun, dup_list)
class(trees) <- "multiPhylo"
trees <- .compressTipLabel(trees)
return(trees)
}
NULL
}
#' @rdname phyDat
#' @export
removeUndeterminedSites <- function(x, ...){
# , use.contrast=TRUE, undetermined=c("?", "n", "-")
nc <- attr(x, "nc")
nr <- attr(x, "nr")
contrast <- attr(x, "contrast")
# if(use.contrast)
ind <- which( (contrast %*% rep(1, nc)) == nc )
# else ind <- sort(match(undetermined, attr(x, "allLevels")))
tmp <- x[[1]] %in% ind
for(i in 2:length(x)) tmp <- tmp & (x[[i]] %in% ind)
if(any(tmp)) x <- getRows(x, (1:nr)[!tmp])
x
}
hasAmbiguousSites <- function(x){
contrast <- attr(x, "contrast")
nc <- as.integer(attr(x, "nc"))
con <- rowSums(contrast > 0) > 1
for (i in seq_along(x)) {
tmp <- con[x[[i]]]
if(any(tmp)) return(TRUE)
}
FALSE
}
#' @rdname phyDat
#' @export
removeAmbiguousSites <- function(x){
contrast <- attr(x, "contrast")
nc <- as.integer(attr(x, "nc"))
con <- rowSums(contrast > 0) < 2
index <- con[x[[1]]]
for (i in 2:length(x)) index <- index & con[x[[i]]]
index <- which(index)
if(length(index)==0) stop('each site contains at least one ambiguous state!')
subset(x, select = index, site.pattern = TRUE)
}
removeParsUninfoSites <- function(data, exact=TRUE){
nr <- attr(data, "nr")
pis <- parsinfo(data, exact)
if (length(pis) > 0){
p0 <- sum(attr(data, "weight")[pis[, 1]] * pis[, 2])
data <- getRows(data, c(1:nr)[-pis[, 1]], TRUE)
if(is.null(attr(data, "informative")))
attr(data, "informative") <- seq_len(nr)[-pis[, 1]]
else attr(data, "informative") <- attr(data, "informative")[-pis[, 1]]
}
else p0 <- 0
if(length(attr(data, "p0"))) p0 <- p0 + attr(data, "p0")
attr(data, "p0") <- p0
data
}
removeParsimonyUninfomativeSites <- function(data, recursive=FALSE, exact=TRUE){
dup_list <- NULL
tmp <- TRUE
star_tree <- FALSE
while (tmp) {
nam <- names(data)
data <- removeParsUninfoSites(data, exact)
if(!recursive) return(data)
if (attr(data, "nr") == 0) {
star_tree <- TRUE
break()
tmp <- FALSE
}
# unique sequences
dup <- map_duplicates(data)
if (!is.null(dup)) {
dup_list <- c(list(dup), dup_list)
data <- subset(data, setdiff(names(data), dup[, 1]), site.pattern=TRUE)
}
else break() # tmp <- FALSE
}
attr(data, "duplicated") <- dup_list
data
}
#' @rdname phyDat
#' @param code The ncbi genetic code number for translation.
#' By default the standard genetic code is used.
#' @export
allSitePattern <- function(n, levels=NULL, names=NULL, type="DNA", code=1){
type <- match.arg(type, c("DNA", "AA", "CODON", "USER"))
if(type=="DNA") levels <- c("a", "c", "g", "t")
if(type=="AA") levels <- c("A", "R", "N", "D", "C", "Q", "E", "G", "H", "I",
"L", "K", "M", "F", "P", "S", "T", "W", "Y", "V")
if(type=="CODON"){
tmp <- .CODON[, as.character(code)]
levels <- rownames(.CODON)
levels <- levels[tmp != "*"]
}
l <- length(levels)
X <- matrix(NA_integer_, n, l^n)
if(is.null(names))rownames(X) <- paste0("t", 1:n)
else rownames(X) <- names
for(i in 1:n)
X[i, ] <- rep(rep(levels, each=l^(i-1)), l^(n-i))
if(type=="DNA") return(phyDat.DNA(X, compress=FALSE, return.index=FALSE))
if(type=="AA") return(phyDat.AA(X, return.index=FALSE))
res <- phyDat.default(X, levels, compress=FALSE, return.index=FALSE)
if(type=="CODON"){
attr(res, "type") <- "CODON"
attr(res, "code") <- code
}
res
}
constSitePattern <- function(n, names=NULL, type="DNA", levels=NULL){
if(type=="DNA"){
levels <- c("a", "c", "g", "t")
l <- 4L
} else if(type=="AA"){
levels <- c("A", "R", "N", "D", "C", "Q", "E", "G", "H", "I", "L", "K", "M",
"F", "P", "S", "T", "W", "Y", "V")
l <- 20L
}
else l <- length(levels)
X <- matrix(0, l, n)
X <- matrix(rep(levels, each=n), n, l)
if(is.null(names)) rownames(X) <- paste0("t", seq_len(n))
else rownames(X) <- names
phyDat(X, type=type, levels=levels)
}
#' Read Amino Acid Sequences in a File
#'
#' This function reads amino acid sequences in a file, and returns a matrix
#' list of DNA sequences with the names of the taxa read in the file as row
#' names.
#'
#'
#' @param file a file name specified by either a variable of mode character, or
#' a double-quoted string.
#' @param format a character string specifying the format of the DNA sequences.
#' Three choices are possible: \code{"interleaved"}, \code{"sequential"}, or
#' \code{"fasta"}, or any unambiguous abbreviation of these.
#' @param skip the number of lines of the input file to skip before beginning
#' to read data.
#' @param nlines the number of lines to be read (by default the file is read
#' until its end).
#' @param comment.char a single character, the remaining of the line after this
#' character is ignored.
#' @param seq.names the names to give to each sequence; by default the names
#' read in the file are used.
#' @return a matrix of amino acid sequences.
#' @author Klaus Schliep \email{klaus.schliep@@gmail.com}
#' @seealso \code{\link[ape]{read.dna}}, \code{\link[ape]{read.GenBank}},
#' \code{\link[phangorn]{phyDat}}, \code{\link[seqinr]{read.alignment}}
#' @references % Anonymous. FASTA format description. %
#' \url{https://en.wikipedia.org/wiki/FASTA_format}
#'
#' Felsenstein, J. (1993) Phylip (Phylogeny Inference Package) version 3.5c.
#' Department of Genetics, University of Washington.
#' \url{https://phylipweb.github.io/phylip/}
#' @keywords IO
#' @noRd
read.aa <- function (file, format = "interleaved", skip = 0, nlines = 0,
comment.char = "#", seq.names = NULL){
getTaxaNames <- function(x) {
x <- sub("^ +", "", x)
x <- sub(" +$", "", x)
x <- sub("^['\"]", "", x)
x <- sub("['\"]$", "", x)
x
}
format <- match.arg(format, c("interleaved", "sequential", "fasta"))
phylip <- if (format %in% c("interleaved", "sequential"))
TRUE
else FALSE
if (format == "fasta") {
obj <- read.FASTA(file, type = "AA")
return(obj)
}
X <- scan(file = file, what = character(), sep = "\n", quiet = TRUE,
skip = skip, nlines = nlines, comment.char = comment.char)
if (phylip) {
fl <- X[1]
oop <- options(warn = -1)
fl.num <- as.numeric(unlist(strsplit(gsub("^ +", "", fl), " +")))
options(oop)
if (all(is.na(fl.num)) || length(fl.num) != 2)
stop("the first line of the file must contain the dimensions of the data")
# if (length(fl.num) != 2)
# stop("the first line of the file must contain the dimensions of the data")
else {
n <- fl.num[1]
s <- fl.num[2]
}
X <- X[-1]
obj <- vector("character", n * s)
dim(obj) <- c(n, s)
}
if (format == "interleaved") {
fl <- X[1]
fl <- unlist(strsplit(fl, NULL))
bases <- grep("[-AaRrNnDdCcQqEeGgHhIiLlKkMmFfPpSsTtWwYyVvBbZzXx?]", fl)
z <- diff(bases)
for (i in seq_along(z)) if (all(z[i:(i + 8)] == 1))
break
start.seq <- bases[i]
if (is.null(seq.names))
seq.names <- getTaxaNames(substr(X[1:n], 1, start.seq - 1))
X[1:n] <- substr(X[1:n], start.seq, nchar(X[1:n]))
X <- gsub(" ", "", X)
nl <- length(X)
for (i in 1:n) obj[i, ] <- unlist(strsplit(X[seq(i, nl, n)], NULL))
}
if (format == "sequential") {
fl <- X[1]
taxa <- character(n)
j <- 1
for (i in 1:n) {
bases <- grep("[-AaRrNnDdCcQqEeGgHhIiLlKkMmFfPpSsTtWwYyVvBbZzXx?]",
unlist(strsplit(X[j], NULL)))
z <- diff(bases)
for (k in seq_along(z)) if (all(z[k:(k + 8)] == 1))
break
start.seq <- bases[k]
taxa[i] <- substr(X[j], 1, start.seq - 1)
sequ <- substr(X[j], start.seq, nchar(X[j]))
sequ <- gsub(" ", "", sequ)
j <- j + 1
while (nchar(sequ) < s) {
sequ <- paste0(sequ, gsub(" ", "", X[j]))
j <- j + 1
}
obj[i, ] <- unlist(strsplit(sequ, NULL))
}
if (is.null(seq.names))
seq.names <- getTaxaNames(taxa)
}
if (phylip) {
rownames(obj) <- seq.names
obj <- tolower(obj)
}
else {
names(obj) <- seq.names
obj <- lapply(obj, tolower)
}
obj
}
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