Commit 6717925a authored by Holger Brandl's avatar Holger Brandl

continued heatmaps

parent f4cf635e
devtools::source_url("http://dl.dropbox.com/u/113630701/rlibs/base-commons.R")
#library(ggplot2)
#library(reshape2)
require.auto(ggdendro)
require.auto(grid)
## Adopted from http://cwcode.wordpress.com/2013/01/30/ggheatmap-version-2/
mydplot <- function(ddata, row=!col, col=!row, labels=col) {
## plot a dendrogram
yrange <- range(ddata$segments$y)
yd <- yrange[2] - yrange[1]
nc <- max(nchar(as.character(ddata$labels$label)))
tangle <- if(row) { 0 } else { 90 }
tshow <- col
p <- ggplot() + geom_segment(data=segment(ddata), aes(x=x, y=y, xend=xend, yend=yend)) +
labs(x = NULL, y = NULL) +
theme_dendro()
if(row) {
p <- p +
scale_x_continuous(expand=c(0.5/length(ddata$labels$x),0)) +
coord_flip()
} else {
p <- p +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
}
return(p)
}
g_legend<-function(a.gplot){
## from
## http://stackoverflow.com/questions/11883844/inserting-a-table-under-the-legend-in-a-ggplot2-histogram
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
##' Display a ggheatmap
##'
##' this function sets up some viewports, and tries to plot the dendrograms to line up with the heatmap
##' @param L a list with 3 named plots: col, row, centre, generated by ggheatmap
##' @param col.width,row.width number between 0 and 1, fraction of the device devoted to the column or row-wise dendrogram. If 0, don't print the dendrogram
##' @return no return value, side effect of displaying plot in current device
##' @export
##' @author Chris Wallace
ggheatmap.show <- function(L, col.width=0.2, row.width=0.2) {
grid.newpage()
top.layout <- grid.layout(nrow = 2, ncol = 2,
widths = unit(c(1-row.width,row.width), "null"),
heights = unit(c(col.width,1-row.width), "null")
)
pushViewport(viewport(layout=top.layout))
if(col.width>0)
print(L$col, vp=viewport(layout.pos.col=1, layout.pos.row=1))
if(row.width>0)
print(L$row, vp=viewport(layout.pos.col=2, layout.pos.row=2))
## print centre without legend
print(L$centre +
theme(
# axis.line=element_blank(),
# axis.text.x=element_blank(),axis.text.y=element_blank(),
# axis.ticks=element_blank(),
# axis.title.x=element_blank(),axis.title.y=element_blank(),
legend.position="none"
# panel.background=element_blank(),
# panel.border=element_blank(),panel.grid.major=element_blank(),
# panel.grid.minor=element_blank(),plot.background=element_blank()
),
vp=viewport(layout.pos.col=1, layout.pos.row=2))
## add legend
legend <- g_legend(L$centre)
pushViewport(viewport(layout.pos.col=2, layout.pos.row=1))
grid.draw(legend)
upViewport(0)
}
##' generate a heatmap + dendrograms, ggplot2 style
##'
##' @param x data matrix
##' @param hm.colours vector of colours (optional)
##' @return invisibly returns a list of ggplot2 objects. Display them with ggheatmap.show()
##' @author Chris Wallace
##' @export
##' @examples
##' ## test run
##' ## simulate data
##' library(mvtnorm)
##' sigma=matrix(0,10,10)
##' sigma[1:4,1:4] <- 0.6
##' sigma[6:10,6:10] <- 0.8
##' diag(sigma) <- 1
##' X <- rmvnorm(n=100,mean=rep(0,10),sigma=sigma)
##'
##' ## make plot
##' p <- ggheatmap(X)
##'
##' ## display plot
##' ggheatmap.show(p)
ggheatmap <- function(x, rowlabels=T, xshift=ifelse(rowlabels, 10, 0), xcompress=10, yshift=3, cluster_method=function(x){ dist(x) %>% hclust("ward") }, fillscale=scale_fill_gradientn(name="log2(sample/N)", colours=c("green", "black", "red"))) {
if(is.null(colnames(x)))
colnames(x) <- sprintf("col%s",1:ncol(x))
if(is.null(rownames(x)))
rownames(x) <- sprintf("row%s",1:nrow(x))
## plot a heatmap
## x is an expression matrix
# row.hc <- hclust(dist(x), "ward.D")
# col.hc <- hclust(dist(t(x)), "ward.D")
# row.dendro <- dendro_data(as.dendrogram(row.hc),type="rectangle")
# col.dendro <- dendro_data(as.dendrogram(col.hc),type="rectangle")
row.dendro <- x %>% cluster_method() %>% as.dendrogram() %>% dendro_data(type="rectangle")
col.dendro <- x %>% t() %>% cluster_method() %>% as.dendrogram() %>% dendro_data(type="rectangle")
## dendro plots
col.plot <- mydplot(col.dendro, col=TRUE, labels=F) +
scale_x_continuous(breaks=NULL) +
theme(plot.margin = unit(c(0, xcompress,0,xcompress+xshift), "mm"))
# scale_x_continuous(breaks = 1:ncol(x),labels=col.hc$labels[col.hc$order]) +
row.plot <- mydplot(row.dendro, row=TRUE, labels=FALSE) +
scale_y_discrete(breaks=NULL) +
theme(plot.margin = unit(c(0,0,2+yshift,0), "mm"))
## order of the dendros
col.ord <- match(col.dendro$labels$label, colnames(x))
row.ord <- match(row.dendro$labels$label, rownames(x))
xx <- x[row.ord,col.ord]
xx <- rownames2column(xx, "rowlabel")
xx <- melt(xx)
# scale_fill_gradientn(colours = hm.colours) +
centre.plot <- ggplot(xx, aes(variable, rowlabel)) +
geom_tile(aes(fill=value)) +
labs(x = NULL, y = NULL) +
scale_x_discrete(expand=c(0,0)) +
theme(plot.margin = unit(c(0,0,2,0), "mm"))+
fillscale +
if(rowlabels) scale_y_discrete(expand=c(0,0)) else scale_y_discrete(expand=c(0,0), breaks=NULL)
ret <- list(col=col.plot,row=row.plot,centre=centre.plot)
invisible(ret)
}
if(F){ #### DEBUG
require.auto(mvtnorm)
sigma=matrix(0,10,10)
sigma[1:4,1:4] <- 0.6
sigma[6:10,6:10] <- 0.8
diag(sigma) <- 1
x <- rmvnorm(n=100,mean=rep(0,10),sigma=sigma)
## display plot
ggheatmap.show(ggheatmap(x, xshift=14))
## other exampel using iris data
ggheatmap.show(ggheatmap(iris %>% select(-Species) %>% as.matrix(), rowlabels=T,xshift=30, xcompress=10))
ggheatmap.show(ggheatmap(iris %>% select(-Species) %>% as.matrix(), rowlabels=F, xc=12, xshift=0) )
} #### DEBUG end
########################################################################################################################
### pca plots (http://largedata.blogspot.de/2011/07/plotting-pca-results-in-ggplot2.html)
makePcaPlot <- function(x = getData(), group = NA, items=rownames(x), title = "") {
require(ggplot2)
require(RColorBrewer)
# data <- x
# data <- t(apply(data, 1, scale))
# rownames(data) <- rownames(x)
# colnames(data) <- colnames(x)
# mydata <- t(data)
mydata <-x
mydata.pca <- prcomp(mydata, retx=TRUE, center=TRUE, scale.=TRUE)
percent <- round((((mydata.pca$sdev)^2 / sum(mydata.pca$sdev^2))*100)[1:2])
scores <- mydata.pca$x
pc12 <- data.frame(PCA1=scores[,1], PCA2=scores[,2], group=group)
# ggplot(pc12, aes(PCA1, PCA2, colour = group)) + geom_point(size = 6, alpha = 3/4)
ggplot(pc12, aes(PCA1, PCA2, colour = group, label=items)) +
geom_point(size = 6, alpha = 3/4) +
geom_text(size = 6, alpha = 3/4) +
xlab(paste("PCA1 (", percent[2], "%)", sep = "")) +
ylab(paste("PCA2 (", percent[2], "%)", sep = ""))
qplot(PCA2, PCA1, geom="blank", main = title, xlab = paste("PCA2 (", percent[2], "%)", sep = ""), ylab = paste("PCA1 (", percent[1], "%)", sep = "")) +
geom_point(aes(colour = group), size = 6, alpha = 3/4)
# theme(
# axis.text.x = element_text(size = base_size * 1.3 , lineheight = 0.9, colour = "grey50", hjust = 1, angle = 90),
# axis.text.y = element_text(size = base_size * 1.3, lineheight = 0.9, colour = "grey50", hjust = 1)
# )
}
makePcaPlot(getData(30,4,2,distort = 0.7), getGroup(30,2))
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