如何使用固定的外部层次结构集群创建热图

Question

我有一个矩阵数据，想要用热图将其可视化。行是物种，所以我想在行旁边显示系统发育树，并根据树重新排列热图的行。我知道R中的heatmap函数可以创建层次聚类热图，但是如何在图中使用我的系统发育聚类而不是默认创建的距离聚类？

Answer 1

首先，您需要使用包ape将数据作为phylo对象读取。

library(ape)
dat <- read.tree(file="your/newick/file")
#or
dat <- read.tree(text="((A:4.2,B:4.2):3.1,C:7.3);")

以下仅适用于您的树是超参数的。

下一步是将您的系统发育树转换为类dendrogram。

以下是一个例子：

data(bird.orders) #This is already a phylo object
hc <- as.hclust(bird.orders) #Compulsory step as as.dendrogram doesn't have a method for phylo objects.
dend <- as.dendrogram(hc)
plot(dend, horiz=TRUE)

mat <- matrix(rnorm(23*23),nrow=23, dimnames=list(sample(bird.orders$tip, 23), sample(bird.orders$tip, 23))) #Some random data to plot

首先，我们需要根据系统发育树中的顺序对矩阵进行排序：

ord.mat <- mat[bird.orders$tip,bird.orders$tip]

然后将其输入heatmap：

heatmap(ord.mat, Rowv=dend, Colv=dend)

编辑：这是一个处理超参数和非超参数树的函数。

heatmap.phylo <- function(x, Rowp, Colp, ...){
    # x numeric matrix
    # Rowp: phylogenetic tree (class phylo) to be used in rows
    # Colp: phylogenetic tree (class phylo) to be used in columns
    # ... additional arguments to be passed to image function
    x <- x[Rowp$tip, Colp$tip]
    xl <- c(0.5, ncol(x)+0.5)
    yl <- c(0.5, nrow(x)+0.5)
    layout(matrix(c(0,1,0,2,3,4,0,5,0),nrow=3, byrow=TRUE),
                  width=c(1,3,1), height=c(1,3,1))
    par(mar=rep(0,4))
    plot(Colp, direction="downwards", show.tip.label=FALSE,
               xlab="",ylab="", xaxs="i", x.lim=xl)
    par(mar=rep(0,4))
    plot(Rowp, direction="rightwards", show.tip.label=FALSE, 
               xlab="",ylab="", yaxs="i", y.lim=yl)
    par(mar=rep(0,4), xpd=TRUE)
    image((1:nrow(x))-0.5, (1:ncol(x))-0.5, x, 
           xaxs="i", yaxs="i", axes=FALSE, xlab="",ylab="", ...)
    par(mar=rep(0,4))
    plot(NA, axes=FALSE, ylab="", xlab="", yaxs="i", xlim=c(0,2), ylim=yl)
    text(rep(0,nrow(x)),1:nrow(x),Rowp$tip, pos=4)
    par(mar=rep(0,4))
    plot(NA, axes=FALSE, ylab="", xlab="", xaxs="i", ylim=c(0,2), xlim=xl)
    text(1:ncol(x),rep(2,ncol(x)),Colp$tip, srt=90, pos=2)
    }

这是前面的（超参数）示例：

heatmap.phylo(mat, bird.orders, bird.orders)

使用非超参数：

cat("owls(((Strix_aluco:4.2,Asio_otus:4.2):3.1,Athene_noctua:7.3):6.3,Tyto_alba:13.5);",
    file = "ex.tre", sep = "\n")
tree.owls <- read.tree("ex.tre")
mat2 <- matrix(rnorm(4*4),nrow=4, 
             dimnames=list(sample(tree.owls$tip,4),sample(tree.owls$tip,4)))
is.ultrametric(tree.owls)
[1] FALSE
heatmap.phylo(mat2,tree.owls,tree.owls)

Answer 2

首先，我创建了一个可重现的示例。没有数据，我们可以猜出你想要什么。所以请下次尝试做得更好（特别是你是确认的用户）。例如，您可以这样做以 newick 格式创建树：

tree.text='(((XXX:4.2,ZZZ:4.2):3.1,HHH:7.3):6.3,AAA:13.6);'

与@plannpus一样，我使用ape将此树转换为hclust类。不幸的是，看起来我们只能为超参数树进行转换：从根到每个尖端的距离是相同的。

library(ape)
tree <- read.tree(text='(((XXX:4.2,ZZZ:4.2):3.1,HHH:7.3):6.3,AAA:13.6);')
is.ultrametric(tree)
hc <- as.hclust.phylo(tree)

然后我使用来自latticeExtra的dendrogramGrob绘制我的树。和来自levelplot的{​​{1}}来绘制热图。

lattice

Answer 3

我改编了plannapus的答案来处理多棵树（也删除了我在此过程中不需要的一些选项）：

library(ape)

heatmap.phylo <- function(x, Rowp, Colp, breaks, col, denscol="cyan", respect=F, ...){
    # x numeric matrix
    # Rowp: phylogenetic tree (class phylo) to be used in rows
    # Colp: phylogenetic tree (class phylo) to be used in columns
    # ... additional arguments to be passed to image function

    scale01 <- function(x, low = min(x), high = max(x)) {
        x <- (x - low)/(high - low)
        x
    }

    col.tip <- Colp$tip
    n.col <- 1
    if (is.null(col.tip)) {
        n.col <- length(Colp)
        col.tip <- unlist(lapply(Colp, function(t) t$tip))
        col.lengths <- unlist(lapply(Colp, function(t) length(t$tip)))
        col.fraction <- col.lengths / sum(col.lengths)
        col.heights <- unlist(lapply(Colp, function(t) max(node.depth.edgelength(t))))
        col.max_height <- max(col.heights)
    }

    row.tip <- Rowp$tip
    n.row <- 1
    if (is.null(row.tip)) {
        n.row <- length(Rowp)
        row.tip <- unlist(lapply(Rowp, function(t) t$tip))
        row.lengths <- unlist(lapply(Rowp, function(t) length(t$tip)))
        row.fraction <- row.lengths / sum(row.lengths)
        row.heights <- unlist(lapply(Rowp, function(t) max(node.depth.edgelength(t))))
        row.max_height <- max(row.heights)
    }

    cexRow <- min(1, 0.2 + 1/log10(n.row))
    cexCol <- min(1, 0.2 + 1/log10(n.col))

    x <- x[row.tip, col.tip]
    xl <- c(0.5, ncol(x)+0.5)
    yl <- c(0.5, nrow(x)+0.5)

    screen_matrix <- matrix( c(
        0,1,4,5,
        1,4,4,5,
        0,1,1,4,
        1,4,1,4,
        1,4,0,1,
        4,5,1,4
    ) / 5, byrow=T, ncol=4 )

    if (respect) {
        r <- grconvertX(1, from = "inches", to = "ndc") / grconvertY(1, from = "inches", to = "ndc")
        if (r < 1) {
            screen_matrix <- screen_matrix * matrix( c(r,r,1,1), nrow=6, ncol=4, byrow=T)
        } else {
            screen_matrix <- screen_matrix * matrix( c(1,1,1/r,1/r), nrow=6, ncol=4, byrow=T)
        }
    }


    split.screen( screen_matrix )

    screen(2)
    par(mar=rep(0,4))

    if (n.col == 1) {
        plot(Colp, direction="downwards", show.tip.label=FALSE,xaxs="i", x.lim=xl)
    } else {
        screens <- split.screen( as.matrix(data.frame( left=cumsum(col.fraction)-col.fraction, right=cumsum(col.fraction), bottom=0, top=1)))
        for (i in 1:n.col) {
            screen(screens[i])
            plot(Colp[[i]], direction="downwards", show.tip.label=FALSE,xaxs="i", x.lim=c(0.5,0.5+col.lengths[i]), y.lim=-col.max_height+col.heights[i]+c(0,col.max_height))
        }
    }

    screen(3)
    par(mar=rep(0,4))

    if (n.col == 1) {
        plot(Rowp, direction="rightwards", show.tip.label=FALSE,yaxs="i", y.lim=yl)
    } else {
        screens <- split.screen( as.matrix(data.frame( left=0, right=1, bottom=cumsum(row.fraction)-row.fraction, top=cumsum(row.fraction))) )
        for (i in 1:n.col) {
            screen(screens[i])
            plot(Rowp[[i]], direction="rightwards", show.tip.label=FALSE,yaxs="i", x.lim=c(0,row.max_height), y.lim=c(0.5,0.5+row.lengths[i]))
        }
    }


    screen(4)
    par(mar=rep(0,4), xpd=TRUE)
    image((1:nrow(x))-0.5, (1:ncol(x))-0.5, x, xaxs="i", yaxs="i", axes=FALSE, xlab="",ylab="", breaks=breaks, col=col, ...)

    screen(6)
    par(mar=rep(0,4))
    plot(NA, axes=FALSE, ylab="", xlab="", yaxs="i", xlim=c(0,2), ylim=yl)
    text(rep(0,nrow(x)),1:nrow(x),row.tip, pos=4, cex=cexCol)

    screen(5)
    par(mar=rep(0,4))
    plot(NA, axes=FALSE, ylab="", xlab="", xaxs="i", ylim=c(0,2), xlim=xl)
    text(1:ncol(x),rep(2,ncol(x)),col.tip, srt=90, adj=c(1,0.5), cex=cexRow)

    screen(1)
    par(mar = c(2, 2, 1, 1), cex = 0.75)

    symkey <- T
    tmpbreaks <- breaks
    if (symkey) {
        max.raw <- max(abs(c(x, breaks)), na.rm = TRUE)
        min.raw <- -max.raw
        tmpbreaks[1] <- -max(abs(x), na.rm = TRUE)
        tmpbreaks[length(tmpbreaks)] <- max(abs(x), na.rm = TRUE)
    } else {
        min.raw <- min(x, na.rm = TRUE)
        max.raw <- max(x, na.rm = TRUE)
    }
    z <- seq(min.raw, max.raw, length = length(col))

    image(z = matrix(z, ncol = 1), col = col, breaks = tmpbreaks, 
          xaxt = "n", yaxt = "n")
    par(usr = c(0, 1, 0, 1))
    lv <- pretty(breaks)
    xv <- scale01(as.numeric(lv), min.raw, max.raw)
    axis(1, at = xv, labels = lv)

    h <- hist(x, plot = FALSE, breaks = breaks)
    hx <- scale01(breaks, min.raw, max.raw)
    hy <- c(h$counts, h$counts[length(h$counts)])
    lines(hx, hy/max(hy) * 0.95, lwd = 1, type = "s", 
          col = denscol)
    axis(2, at = pretty(hy)/max(hy) * 0.95, pretty(hy))
    par(cex = 0.5)
    mtext(side = 2, "Count", line = 2)

    close.screen(all.screens = T)

}

tree <- read.tree(text = "(A:1,B:1);((C:1,D:2):2,E:1);((F:1,G:1,H:2):5,((I:1,J:2):2,K:1):1);", comment.char="")
N <- sum(unlist(lapply(tree, function(t) length(t$tip))))

set.seed(42)
m <- cor(matrix(rnorm(N*N), nrow=N))
rownames(m) <- colnames(m) <- LETTERS[1:N]
heatmap.phylo(m, tree, tree, col=bluered(10), breaks=seq(-1,1,length.out=11), respect=T) 

Answer 4

热像图的这种确切应用已在the plot_heatmap function ggplot2 the phyloseq package中openly/freely developed on GitHub实施，http://joey711.github.io/phyloseq/plot_heatmap-examples。这里包含完整代码和结果的示例：

an article about the NeatMap package

有一点需要注意，而不是您在此明确要求的内容，但phyloseq::plot_heatmap不会覆盖任一轴的分层树。有一个很好的理由不将轴排序基于层次聚类 - 这是因为长分支末端的索引仍然可以任意相邻，具体取决于分支的方式在节点处旋转。这一点，以及基于非度量多维缩放的替代方案在{{3}}中进一步解释，它也是为R编写的并使用ggplot2。这种用于对热图中的指数进行排序的降维（排序）方法适用于phyloseq::plot_heatmap中的系统发育丰度数据。

Answer 5

虽然我对phlyoseq::plot_heatmap的建议可以帮助你解决问题，但强大的“ggtree”软件包可以做到这一点，或者更多，如果在树上表示数据真的是你想要的那样。

以下ggtree文档页面顶部显示了一些示例：

http://www.bioconductor.org/packages/3.7/bioc/vignettes/ggtree/inst/doc/advanceTreeAnnotation.html

请注意，我根本不隶属于ggtree dev。只是该项目的粉丝以及它已经可以做的事情。

Answer 6

与@plannapus进行通信后，我已经修改了（仅几处）代码，以删除上述代码中的一些额外xlab=""信息。 在这里您将找到代码。您可以看到带有额外代码的注释行，现在新行仅删除了它们。 希望这可以帮助像我这样的新用户！ ：）

heatmap.phylo <- function(x, Rowp, Colp, ...){
    # x numeric matrix
    # Rowp: phylogenetic tree (class phylo) to be used in rows
    # Colp: phylogenetic tree (class phylo) to be used in columns
    # ... additional arguments to be passed to image function
    x <- x[Rowp$tip, Colp$tip]
    xl <- c(0.5, ncol(x) + 0.5)
    yl <- c(0.5, nrow(x) + 0.5)
    layout(matrix(c(0,1,0,2,3,4,0,5,0),nrow = 3, byrow = TRUE),
                  width = c(1,3,1), height = c(1,3,1))
    par(mar = rep(0,4))
    # plot(Colp, direction = "downwards", show.tip.label = FALSE,
    #            xlab = "", ylab = "", xaxs = "i", x.lim = xl)
      plot(Colp, direction = "downwards", show.tip.label = FALSE,
               xaxs = "i", x.lim = xl)
    par(mar = rep(0,4))
    # plot(Rowp, direction = "rightwards", show.tip.label = FALSE, 
    #            xlab = "", ylab = "", yaxs = "i", y.lim = yl)
    plot(Rowp, direction = "rightwards", show.tip.label = FALSE, 
               yaxs = "i", y.lim = yl)
    par(mar = rep(0,4), xpd = TRUE)
    image((1:nrow(x)) - 0.5, (1:ncol(x)) - 0.5, x, 
           #xaxs = "i", yaxs = "i", axes = FALSE, xlab = "", ylab = "", ...)
           xaxs = "i", yaxs = "i", axes = FALSE, ...)
    par(mar = rep(0,4))
    plot(NA, axes = FALSE, ylab = "", xlab = "", yaxs = "i", xlim = c(0,2), ylim = yl)
    text(rep(0, nrow(x)), 1:nrow(x), Rowp$tip, pos = 4)
    par(mar = rep(0,4))
    plot(NA, axes = FALSE, ylab = "", xlab = "", xaxs = "i", ylim = c(0,2), xlim = xl)
    text(1:ncol(x), rep(2, ncol(x)), Colp$tip, srt = 90, pos = 2)
}