## dist.topo.R (2012-03-13) ## Topological Distances, Tree Bipartitions, ## Consensus Trees, and Bootstrapping Phylogenies ## Copyright 2005-2012 Emmanuel Paradis ## This file is part of the R-package `ape'. ## See the file ../COPYING for licensing issues. dist.topo <- function(x, y, method = "PH85") { if (method == "score" && (is.null(x$edge.length) || is.null(y$edge.length))) stop("trees must have branch lengths for branch score distance.") nx <- length(x$tip.label) x <- unroot(x) y <- unroot(y) bp1 <- .Call("bipartition", x$edge, nx, x$Nnode, PACKAGE = "ape") bp1 <- lapply(bp1, function(xx) sort(x$tip.label[xx])) ny <- length(y$tip.label) # fix by Otto Cordero ## fix by Tim Wallstrom: bp2.tmp <- .Call("bipartition", y$edge, ny, y$Nnode, PACKAGE = "ape") bp2 <- lapply(bp2.tmp, function(xx) sort(y$tip.label[xx])) bp2.comp <- lapply(bp2.tmp, function(xx) setdiff(1:ny, xx)) bp2.comp <- lapply(bp2.comp, function(xx) sort(y$tip.label[xx])) ## End q1 <- length(bp1) q2 <- length(bp2) if (method == "PH85") { p <- 0 for (i in 1:q1) { for (j in 1:q2) { if (identical(bp1[[i]], bp2[[j]]) | identical(bp1[[i]], bp2.comp[[j]])) { p <- p + 1 break } } } dT <- q1 + q2 - 2 * p # same than: ##dT <- if (q1 == q2) 2*(q1 - p) else 2*(min(q1, q2) - p) + abs(q1 - q2) } if (method == "score") { dT <- 0 found1 <- FALSE found2 <- logical(q2) found2[1] <- TRUE for (i in 2:q1) { for (j in 2:q2) { if (identical(bp1[[i]], bp2[[j]]) | identical(bp1[[i]], bp2.comp[[j]])) { dT <- dT + (x$edge.length[which(x$edge[, 2] == nx + i)] - y$edge.length[which(y$edge[, 2] == ny + j)])^2 found1 <- found2[j] <- TRUE break } } if (found1) found1 <- FALSE else dT <- dT + (x$edge.length[which(x$edge[, 2] == nx + i)])^2 } if (!all(found2)) dT <- dT + sum((y$edge.length[y$edge[, 2] %in% (ny + which(!found2))])^2) dT <- sqrt(dT) } dT } .compressTipLabel <- function(x) { ## 'x' is a list of objects of class "phylo" possibly with no class if (!is.null(attr(x, "TipLabel"))) return(x) ref <- x[[1]]$tip.label if (any(table(ref) != 1)) stop("some tip labels are duplicated in tree no. 1") n <- length(ref) Ntree <- length(x) if (Ntree > 1) { for (i in 2:Ntree) { label <- x[[i]]$tip.label if (!identical(label, ref)) { if (length(label) != length(ref)) stop(paste("tree no.", i, "has a different number of tips")) ilab <- match(label, ref) ## can use tabulate here because 'ilab' contains integers if (any(is.na(ilab))) stop(paste("tree no.", i, "has different tip labels")) ### the test below does not seem useful anymore ### if (any(tabulate(ilab) > 1)) ### stop(paste("some tip labels are duplicated in tree no.", i)) ### ie <- match(1:n, x[[i]]$edge[, 2]) x[[i]]$edge[ie, 2] <- ilab } x[[i]]$tip.label <- NULL } } x[[1]]$tip.label <- NULL attr(x, "TipLabel") <- ref x } prop.part <- function(..., check.labels = TRUE) { obj <- list(...) if (length(obj) == 1 && class(obj[[1]]) != "phylo") obj <- obj[[1]] ## ## class(obj) <- NULL # needed? apparently not, see below (2010-11-18) ## ntree <- length(obj) if (ntree == 1) check.labels <- FALSE if (check.labels) obj <- .compressTipLabel(obj) # fix by Klaus Schliep (2011-02-21) for (i in 1:ntree) storage.mode(obj[[i]]$Nnode) <- "integer" ## ## The 1st must have tip labels ## Maybe simply pass the number of tips to the C code?? obj <- .uncompressTipLabel(obj) # fix a bug (2010-11-18) ## clades <- .Call("prop_part", obj, ntree, TRUE, PACKAGE = "ape") attr(clades, "number") <- attr(clades, "number")[1:length(clades)] attr(clades, "labels") <- obj[[1]]$tip.label class(clades) <- "prop.part" clades } print.prop.part <- function(x, ...) { if (is.null(attr(x, "labels"))) { for (i in 1:length(x)) { cat("==>", attr(x, "number")[i], "time(s):") print(x[[i]], quote = FALSE) } } else { for (i in 1:length(attr(x, "labels"))) cat(i, ": ", attr(x, "labels")[i], "\n", sep = "") cat("\n") for (i in 1:length(x)) { cat("==>", attr(x, "number")[i], "time(s):") print(x[[i]], quote = FALSE) } } } summary.prop.part <- function(object, ...) attr(object, "number") plot.prop.part <- function(x, barcol = "blue", leftmar = 4, ...) { if (is.null(attr(x, "labels"))) stop("cannot plot this partition object; see ?prop.part for details.") L <- length(x) n <- length(attr(x, "labels")) layout(matrix(1:2, 2, 1), heights = c(1, 3)) par(mar = c(0.1, leftmar, 0.1, 0.1)) plot(1:L, attr(x, "number"), type = "h", col = barcol, xlim = c(1, L), xlab = "", ylab = "Frequency", xaxt = "n", bty = "n") plot(0, type = "n", xlim = c(1, L), ylim = c(1, n), xlab = "", ylab = "", xaxt = "n", yaxt = "n") for (i in 1:L) points(rep(i, length(x[[i]])), x[[i]], ...) mtext(attr(x, "labels"), side = 2, at = 1:n, las = 1) } prop.clades <- function(phy, ..., part = NULL, rooted = FALSE) { if (is.null(part)) { ## ## Are we going to keep the '...' way of passing trees? obj <- list(...) if (length(obj) == 1 && class(obj[[1]]) != "phylo") obj <- unlist(obj, recursive = FALSE) ## part <- prop.part(obj, check.labels = TRUE) } bp <- prop.part(phy) if (!rooted) { bp <- postprocess.prop.part(bp) part <- postprocess.prop.part(part) # fix by Klaus Schliep ## actually the above line in not needed if called from boot.phylo() } n <- numeric(phy$Nnode) for (i in seq_along(bp)) { for (j in seq_along(part)) { ## we rely on the fact the values returned by prop.part are ## sorted and without attributes, so identical can be used: if (identical(bp[[i]], part[[j]])) { n[i] <- attr(part, "number")[j] done <- TRUE break } } } n } boot.phylo <- function(phy, x, FUN, B = 100, block = 1, trees = FALSE, quiet = FALSE, rooted = FALSE) { if (is.list(x) && !is.data.frame(x)) { if (inherits(x, "DNAbin")) x <- as.matrix(x) else { nm <- names(x) n <- length(x) x <- unlist(x) nL <- length(x) x <- matrix(x, n, nL/n, byrow = TRUE) rownames(x) <- nm } } boot.tree <- vector("list", B) if (!quiet) # suggestion by Alastair Potts progbar <- utils::txtProgressBar(style = 3) for (i in 1:B) { if (block > 1) { y <- seq(block, ncol(x), block) boot.i <- sample(y, replace = TRUE) boot.samp <- numeric(ncol(x)) boot.samp[y] <- boot.i for (j in 1:(block - 1)) boot.samp[y - j] <- boot.i - j } else boot.samp <- sample(ncol(x), replace = TRUE) boot.tree[[i]] <- FUN(x[, boot.samp]) if (!quiet) utils::setTxtProgressBar(progbar, i/B) } if (!quiet) close(progbar) for (i in 1:B) storage.mode(boot.tree[[i]]$Nnode) <- "integer" storage.mode(phy$Nnode) <- "integer" pp <- prop.part(boot.tree) if (!rooted) pp <- postprocess.prop.part(pp) ans <- prop.clades(phy, part = pp, rooted = rooted) ##ans <- attr(.Call("prop_part", c(list(phy), boot.tree), ## B + 1, FALSE, PACKAGE = "ape"), "number") - 1 if (trees) { class(boot.tree) <- "multiPhylo" ans <- list(BP = ans, trees = boot.tree) } ans } ### The next function transforms an object of class "prop.part" so ### that the vectors which are identical in terms of split are aggregated. ### For instance if n = 5 tips, 1:2 and 3:5 actually represent the same ### split though they are different clades. The aggregation is done ### arbitrarily. The call to ONEwise() insures that all splits include ### the first tip. postprocess.prop.part <- function(x) { n <- length(x[[1]]) N <- length(x) w <- attr(x, "number") drop <- logical(N) V <- numeric(n) for (i in 2:(N - 1)) { if (drop[i]) next A <- x[[i]] for (j in (i + 1):N) { if (drop[j]) next B <- x[[j]] if (length(A) + length(B) != n) next V[] <- 0L V[A] <- 1L V[B] <- 1L if (all(V == 1L)) { drop[j] <- TRUE w[i] <- w[i] + w[j] } } } if (any(drop)) { labels <- attr(x, "labels") x <- x[!drop] w <- w[!drop] attr(x, "number") <- w attr(x, "labels") <- labels class(x) <- "prop.part" } ONEwise(x) } ### This function changes an object of class "prop.part" so that they ### all include the first tip. For instance if n = 5 tips, 3:5 is ### changed to 1:2. ONEwise <- function(x) { n <- length(x[[1L]]) v <- 1:n for (i in 2:length(x)) { y <- x[[i]] if (y[1] != 1) x[[i]] <- v[-y] } x } consensus <- function(..., p = 1, check.labels = TRUE) { foo <- function(ic, node) { ## ic: index of 'pp' ## node: node number in the final tree pool <- pp[[ic]] if (ic < m) { for (j in (ic + 1):m) { wh <- match(pp[[j]], pool) if (!any(is.na(wh))) { edge[pos, 1] <<- node pool <- pool[-wh] edge[pos, 2] <<- nextnode <<- nextnode + 1L pos <<- pos + 1L foo(j, nextnode) } } } size <- length(pool) if (size) { ind <- pos:(pos + size - 1) edge[ind, 1] <<- node edge[ind, 2] <<- pool pos <<- pos + size } } obj <- list(...) if (length(obj) == 1) { ## better than unlist(obj, recursive = FALSE) ## because "[[" keeps the class of 'obj': obj <- obj[[1]] if (class(obj) == "phylo") return(obj) } if (!is.null(attr(obj, "TipLabel"))) labels <- attr(obj, "TipLabel") else { labels <- obj[[1]]$tip.label if (check.labels) obj <- .compressTipLabel(obj) } ntree <- length(obj) ## Get all observed partitions and their frequencies: pp <- prop.part(obj, check.labels = FALSE) ## Drop the partitions whose frequency is less than 'p': if (p == 0.5) p <- 0.5000001 # avoid incompatible splits pp <- pp[attr(pp, "number") >= p * ntree] ## Get the order of the remaining partitions by decreasing size: ind <- sort(unlist(lapply(pp, length)), decreasing = TRUE, index.return = TRUE)$ix pp <- pp[ind] n <- length(labels) m <- length(pp) edge <- matrix(0L, n + m - 1, 2) if (m == 1) { edge[, 1] <- n + 1L edge[, 2] <- 1:n } else { nextnode <- n + 1L pos <- 1L foo(1, nextnode) } structure(list(edge = edge, tip.label = labels, Nnode = m), class = "phylo") }