R/generate_heatmap.R
In schyen/somefxns: Generic Tools to Help with Analysis
Defines functions
generate_heatmap
Documented in
generate_heatmap
#' explore_heatmap.R
#'
#' Produce heatmap of count data. uses euclidean distances (recommdended) of clr transformed data; zero replacement completed by Bayesian-multiplicative replacement
#'
#' @param data dataframe. long format, with column of xdata, variable
#' (such as taxonomy, or compounds), and value (such as abundance or concentration)
#' @param x_var string. variable to be heatmap x-axis. example: sample
#' should be a column name in data
#' @param y_var string. variable to be heatmap y-axis. example: species or compound
#' should be column name in data
#' @param value_var string. column containing heatmap values
#' @param x_dist string; dist method for x dendrogram;
#' method for computing phylogenetic distance;
#' supplied to the dist(); default method: "euclidean"
#' dist method options: "euclidean", "maximum", "manhattan",
#' "canberra", "binary" or "minkowski"
#' @param x_hclust string; hclust method for x dendrogram;
#' Linkage criteria to determine distance between sets of
#' observations; to be used in hclust(); default method: "complete"
#' hclust method options:"ward.D", "ward.D2", "single", "complete",
#' "average" (= UPGMA), "mcquitty" (= WPGMA),
#' "median" (= WPGMC) or "centroid" (= UPGMC)
#' @param y_dist string; dist method for ydata dendrogram;
#' method for computing phylogenetic distance;
#' supplied to the dist(); default method: "euclidean"
#' dist method options: "euclidean", "maximum", "manhattan",
#' "canberra", "binary" or "minkowski"
#' @param y_hclust string; hclust method for ydata dendrogram;
#' Linkage criteria to determine distance between sets of
#' observations; to be used in hclust(); default method: "complete"
#' hclust method options:"ward.D", "ward.D2", "single", "complete",
#' "average" (= UPGMA), "mcquitty" (= WPGMA),
#' "median" (= WPGMC) or "centroid" (= UPGMC)
#' When set to FALSE, xdata listed along y-axis
#' @param x_meta dataframe. default NULL. Any metadata on heatmap x axis
#' variable (such as sample) to be included
#' x_var should be the identifier to link metadata
#' @param y_meta dataframe. default NULL. any metadata on heatmap y axis
#' variable (such as species) to be included
#' y_var should be identifier to link metadata
#' @param x_label string. default NULL. Should be column in x_meta.
#' How x-axis of heatmap should be labelled. When set to NULL, x_var is used
#' @param y_label string. default NULL. Should be a column in y_meta.
#' How y-axis of heatmap should be labelled. When set to NULL, y_var is used
#' @param heatmap_w numeric; default 20; width (cm) of heatmap panel
#' @param heatmap_h numeric; default 20; height (cm) of heatmap panel
#' @param dendro_x_h numeric; default 8; height (cm) of x-axis dendrogram;
#' helps with ensuring x-axis dendrogram labels are not cut off
#' @param dendro_y_w numeric; default 8; width(cm) of y-axis dendrogram;
#' helps with ensuring y-axis dendrogram labels are not cut off
#' @param output = string; path and file name of resulting heatmap png
#' Example: "/path/to/my_heatmap.png"
#' @return
#' \code{pdata} dataframe for heatmap
#' \code{ddata_x} dataframe for x-axis dendrogram
#' \code{ddata_x} dataframe for y-axis dendrogram
#' \code{p_hl} ggplot of heatmap and legend
#' \code{p_x} ggplot of x-axis dendrogram
#' \code{p_y} ggplot of y-axis dendrogram
#' \code{g} gtable grob of entire heatmap and dendrograms
#' @import ggplot2
generate_heatmap <- function(data, x_var, y_var, value_var,
x_dist = 'euclidean', x_hclust = 'complete',
y_dist = 'euclidean', y_hclust = 'complete',
x_meta = NULL, y_meta = NULL,
x_label = NULL, y_label = NULL,
heatmap_w = 20, heatmap_h = 20,
dendro_x_h = 8, dendro_y_w = 8,
output) {
# formatting data into wide format so can calculate dendrograms
## heatmap x-axis data
form <- as.formula(paste(x_var, y_var, sep = "~"))
xdata <- reshape2::dcast(data, formula = form, value.var = value_var)
# setting rownames
row.names(xdata) <- xdata[ , x_var]
xdata <- xdata[ ,colnames(xdata) != x_var]
## heatmap y-axis data
form <- as.formula(paste(y_var, x_var, sep = "~"))
ydata <- reshape2::dcast(data, formula = form, value.var = value_var)
row.names(ydata) <- ydata[, y_var]
ydata <- ydata[, colnames(ydata) != y_var]
# calculating dendrograms------------------------------------------------------
dd_xdata <- as.dendrogram(hclust(dist(xdata, method=x_dist), # x as row
method=x_hclust))
ord_xdata <- order.dendrogram(dd_xdata)
dd_ydata <- as.dendrogram(hclust(dist(ydata, method=y_dist), # ydata as row
method=y_hclust))
ord_ydata <- order.dendrogram(dd_ydata)
# extracting dendrogram data
ddata_x <- ggdendro::dendro_data(dd_xdata)
ddata_y <- ggdendro::dendro_data(dd_ydata)
# reading in metadata if necessary--------------------------------------------
if(!is.null(x_meta)) {
if(is.null(x_label)) {
stop("x_label must not be null when x_meta is specified")
}
# copying dendrogram labels
new_x_lab <- ggdendro::label(ddata_x)
new_x_lab$label <- as.character(new_x_lab$label)
colnames(new_x_lab)[3] <- x_var
# adding x_label
new_x_lab <- dplyr::inner_join(new_x_lab, x_meta, by=x_var)
# resetting strain dendrogram labels to taxonomy (or strain number)
ddata_x$label <- new_x_lab[, x_label]
}
if(!is.null(y_meta)) {
if(is.null(y_label)) {
stop("y_label must not be null when y_meta is specified")
}
# copying dendrogram labels
new_y_lab <- ggdendro::label(ddata_y)
new_y_lab$label <- as.character(new_y_lab$label)
colnames(new_y_lab)[3] <- y_var
# adding y_label
new_y_lab <- dplyr::inner_join(new_y_lab, y_meta, by=y_var)
# resetting strain dendrogram labels to taxonomy (or strain number)
ddata_y$label <- new_y_lab[, y_label]
}
# heatmap data-----------------------------------------------------------------
ddata <- xdata[ord_xdata, ord_ydata]
# column for sample names, to set order
ddata$sampleID <- rownames(ddata)
ddata$sampleID <- with(ddata, factor(sampleID, levels=sampleID,
ordered=TRUE))
# melting for ggplot
pdata <- reshape2::melt(ddata, id.vars = x_var, variable.name = y_var,
value.name = value_var)
## Set up a blank theme--------------------------------------------------------
theme_none <- function() {
ggplot2::theme(
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_blank(),
axis.title.x = ggplot2::element_text(colour=NA),
axis.title.y = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank(),
axis.line = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank()
)
}
# creating heatmap--------------------------------------------------------------
p_h <- ggplot2::ggplot(pdata, ggplot2::aes_string(x=x_var, y=y_var))
p_hl <- p_h +
ggplot2::geom_tile(ggplot2::aes_string(fill=value_var)) +
ggplot2::scale_fill_gradient2(low = "#9A0038", mid = "#FFFFFF", high = "#003AC3",
midpoint=0,
breaks=c(ceiling(min(pdata[,value_var])), 0,
floor(max(pdata[, value_var]))),
ggplot2::guide_legend(title='Normalized Count')) +
ggplot2::theme(panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
plot.margin = ggplot2::margin(0,0,0,0, 'cm'),
legend.direction='horizontal')
# remove legend from p_hl
p_h <- p_hl + ggplot2::theme(legend.position='none')
## X axis dendrogram 1----------------------------------------------------------
# calculating plot limits
xlim <- range(c(ggdendro::segment(ddata_x)$x, ggdendro::segment(ddata_x)$xend))
ylim <- range(c(ggdendro::segment(ddata_x)$y, ggdendro::segment(ddata_x)$yend))
x_name <- as.character(ggdendro::label(ddata_x)$label)
name_len <- lapply(x_name, function(x) nchar(x))
name_len <- unlist(name_len)
name_len <- max(name_len)
xadjust <- name_len*0.75
xmin <- floor(xlim[1]) - 0.5
xmax <- ceiling(xlim[2])+ 0.5
xlim <- c(xmin, xmax)
ymin <- floor(ylim[1]) - xadjust
ymax <- ceiling(ylim[2]) + 1
ylim <- c(ymin, ymax)
# plotting x-axis dendrogram
p_x <- ggplot2::ggplot() +
ggplot2::geom_segment(data=ddata_x$segment,
ggplot2::aes(x = x, y = y, xend = xend, yend = yend)) +
ggplot2::geom_text(data=ddata_x$labels, ggplot2::aes(x=x, y=y, label=label),
angle=-90, hjust=0, vjust=0.3) +
ggplot2::scale_x_continuous(expand = c(0, 0), limits=xlim) +
ggplot2::scale_y_continuous(expand = c(0, 0), limits=ylim) +
theme_none() +
ggplot2::theme(plot.margin = ggplot2::unit(c(0,0.2,0,0.5), 'cm')) +#t,r,b,l
ggplot2::labs(x=NULL, y=NULL)
## Y axis dendrogram 2----------------------------------------------------------
# calculating plot limits
xlim <- range(c(ggdendro::segment(ddata_y)$x, ggdendro::segment(ddata_y)$xend))
ylim <- range(c(ggdendro::segment(ddata_y)$y, ggdendro::segment(ddata_y)$yend))
ydata_name <- as.character(ggdendro::label(ddata_y)$label)
name_len <- lapply(ydata_name, function(x) nchar(x))
name_len <- unlist(name_len)
name_len <- max(name_len)
yadjust <- name_len*1.6
xmin <- floor(xlim[1]) - 0.5
xmax <- ceiling(xlim[2]) + 0.5
xlim <- c(xmin, xmax)
ymin <- floor(ylim[1]) - yadjust
ymax <- ceiling(ylim[2])
ylim <- c(ymin, ymax)
# plotting y-axis dendrogram
p_y <- ggplot2::ggplot() +
ggplot2::geom_segment(data=ddata_y$segment,
ggplot2::aes(x = x, y = y, xend = xend, yend = yend)) +
ggplot2::geom_text(data=ddata_y$labels, ggplot2::aes(x=x, y=y, label=label),
hjust=1, vjust=0.5) +
ggplot2::coord_flip() +
ggplot2::scale_x_continuous(expand = c(0, 0), limits=xlim) +
ggplot2::scale_y_continuous(expand = c(0, 0), limits=ylim) +
theme_none() +
ggplot2::theme(plot.margin = ggplot2::unit(c(-0.1,0,0.6,0), 'cm')) +
ggplot2::labs(x=NULL, y=NULL)
# plot caption
x_dist <- x_dist
x_hclust <- x_hclust
y_dist <- y_dist
y_hclust <- y_hclust
caption <- stringr::str_c(sprintf("X-Axis Dendrogram:\n Distance method: %s\n Linkage method: %s\n\n",x_dist, x_hclust),
sprintf("Y-Axis Dendrogram:\n Distance method: %s\n Linkage method: %s", y_dist, y_hclust))
# putting plots together--------------------------------------------------------
# extracting legend
g_hl <- ggplot2::ggplotGrob(p_hl)
legend <- grep("guide", g_hl$layout$name)
g_l <- g_hl[["grobs"]][[legend]]
# putting legend and captions together
g_c <- grid::textGrob(label=caption, x=0.2, y=0.3, just='left')
g_cl <- gridExtra::grid.arrange(g_c, g_l, ncol=1)
# converting plots to grobs
g_h <- ggplot2::ggplotGrob(p_h)
g_x <- ggplot2::ggplotGrob(p_x)
g_y <- ggplot2::ggplotGrob(p_y)
mat <- matrix(list(g_x, g_h, g_cl, g_y), nrow=2)
g <- gtable::gtable_matrix(name='heatmap',grobs=mat,
widths=ggplot2::unit(c(heatmap_w,dendro_y_w),'cm'),
heights=ggplot2::unit(c(dendro_x_h, heatmap_h), 'cm'))
# saving plot
ggplot2::ggsave(out, g, width=(heatmap_w+dendro_y_w)*1.01,
height=(heatmap_h+dendro_x_h)*1.01, unit='cm')
msg <- sprintf("\nSaving heatmap:\n%s", out)
message(msg)
return(list('pdata'=pdata, 'ddata_x'=ddata_x,
'ddata_x'=ddata_x, 'p_hl'=p_hl,'p_x'=p_x,'p_y'=p_y,
'g' = g))
}
schyen/somefxns documentation built on Aug. 6, 2019, 2:26 p.m.
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Defines functions generate_heatmap
Documented in generate_heatmap
#' explore_heatmap.R
#'
#' Produce heatmap of count data. uses euclidean distances (recommdended) of clr transformed data; zero replacement completed by Bayesian-multiplicative replacement
#'
#' @param data dataframe. long format, with column of xdata, variable
#' (such as taxonomy, or compounds), and value (such as abundance or concentration)
#' @param x_var string. variable to be heatmap x-axis. example: sample
#' should be a column name in data
#' @param y_var string. variable to be heatmap y-axis. example: species or compound
#' should be column name in data
#' @param value_var string. column containing heatmap values
#' @param x_dist string; dist method for x dendrogram;
#' method for computing phylogenetic distance;
#' supplied to the dist(); default method: "euclidean"
#' dist method options: "euclidean", "maximum", "manhattan",
#' "canberra", "binary" or "minkowski"
#' @param x_hclust string; hclust method for x dendrogram;
#' Linkage criteria to determine distance between sets of
#' observations; to be used in hclust(); default method: "complete"
#' hclust method options:"ward.D", "ward.D2", "single", "complete",
#' "average" (= UPGMA), "mcquitty" (= WPGMA),
#' "median" (= WPGMC) or "centroid" (= UPGMC)
#' @param y_dist string; dist method for ydata dendrogram;
#' method for computing phylogenetic distance;
#' supplied to the dist(); default method: "euclidean"
#' dist method options: "euclidean", "maximum", "manhattan",
#' "canberra", "binary" or "minkowski"
#' @param y_hclust string; hclust method for ydata dendrogram;
#' Linkage criteria to determine distance between sets of
#' observations; to be used in hclust(); default method: "complete"
#' hclust method options:"ward.D", "ward.D2", "single", "complete",
#' "average" (= UPGMA), "mcquitty" (= WPGMA),
#' "median" (= WPGMC) or "centroid" (= UPGMC)
#' When set to FALSE, xdata listed along y-axis
#' @param x_meta dataframe. default NULL. Any metadata on heatmap x axis
#' variable (such as sample) to be included
#' x_var should be the identifier to link metadata
#' @param y_meta dataframe. default NULL. any metadata on heatmap y axis
#' variable (such as species) to be included
#' y_var should be identifier to link metadata
#' @param x_label string. default NULL. Should be column in x_meta.
#' How x-axis of heatmap should be labelled. When set to NULL, x_var is used
#' @param y_label string. default NULL. Should be a column in y_meta.
#' How y-axis of heatmap should be labelled. When set to NULL, y_var is used
#' @param heatmap_w numeric; default 20; width (cm) of heatmap panel
#' @param heatmap_h numeric; default 20; height (cm) of heatmap panel
#' @param dendro_x_h numeric; default 8; height (cm) of x-axis dendrogram;
#' helps with ensuring x-axis dendrogram labels are not cut off
#' @param dendro_y_w numeric; default 8; width(cm) of y-axis dendrogram;
#' helps with ensuring y-axis dendrogram labels are not cut off
#' @param output = string; path and file name of resulting heatmap png
#' Example: "/path/to/my_heatmap.png"
#' @return
#' \code{pdata} dataframe for heatmap
#' \code{ddata_x} dataframe for x-axis dendrogram
#' \code{ddata_x} dataframe for y-axis dendrogram
#' \code{p_hl} ggplot of heatmap and legend
#' \code{p_x} ggplot of x-axis dendrogram
#' \code{p_y} ggplot of y-axis dendrogram
#' \code{g} gtable grob of entire heatmap and dendrograms
#' @import ggplot2
generate_heatmap <- function(data, x_var, y_var, value_var,
x_dist = 'euclidean', x_hclust = 'complete',
y_dist = 'euclidean', y_hclust = 'complete',
x_meta = NULL, y_meta = NULL,
x_label = NULL, y_label = NULL,
heatmap_w = 20, heatmap_h = 20,
dendro_x_h = 8, dendro_y_w = 8,
output) {
# formatting data into wide format so can calculate dendrograms
## heatmap x-axis data
form <- as.formula(paste(x_var, y_var, sep = "~"))
xdata <- reshape2::dcast(data, formula = form, value.var = value_var)
# setting rownames
row.names(xdata) <- xdata[ , x_var]
xdata <- xdata[ ,colnames(xdata) != x_var]
## heatmap y-axis data
form <- as.formula(paste(y_var, x_var, sep = "~"))
ydata <- reshape2::dcast(data, formula = form, value.var = value_var)
row.names(ydata) <- ydata[, y_var]
ydata <- ydata[, colnames(ydata) != y_var]
# calculating dendrograms------------------------------------------------------
dd_xdata <- as.dendrogram(hclust(dist(xdata, method=x_dist), # x as row
method=x_hclust))
ord_xdata <- order.dendrogram(dd_xdata)
dd_ydata <- as.dendrogram(hclust(dist(ydata, method=y_dist), # ydata as row
method=y_hclust))
ord_ydata <- order.dendrogram(dd_ydata)
# extracting dendrogram data
ddata_x <- ggdendro::dendro_data(dd_xdata)
ddata_y <- ggdendro::dendro_data(dd_ydata)
# reading in metadata if necessary--------------------------------------------
if(!is.null(x_meta)) {
if(is.null(x_label)) {
stop("x_label must not be null when x_meta is specified")
}
# copying dendrogram labels
new_x_lab <- ggdendro::label(ddata_x)
new_x_lab$label <- as.character(new_x_lab$label)
colnames(new_x_lab)[3] <- x_var
# adding x_label
new_x_lab <- dplyr::inner_join(new_x_lab, x_meta, by=x_var)
# resetting strain dendrogram labels to taxonomy (or strain number)
ddata_x$label <- new_x_lab[, x_label]
}
if(!is.null(y_meta)) {
if(is.null(y_label)) {
stop("y_label must not be null when y_meta is specified")
}
# copying dendrogram labels
new_y_lab <- ggdendro::label(ddata_y)
new_y_lab$label <- as.character(new_y_lab$label)
colnames(new_y_lab)[3] <- y_var
# adding y_label
new_y_lab <- dplyr::inner_join(new_y_lab, y_meta, by=y_var)
# resetting strain dendrogram labels to taxonomy (or strain number)
ddata_y$label <- new_y_lab[, y_label]
}
# heatmap data-----------------------------------------------------------------
ddata <- xdata[ord_xdata, ord_ydata]
# column for sample names, to set order
ddata$sampleID <- rownames(ddata)
ddata$sampleID <- with(ddata, factor(sampleID, levels=sampleID,
ordered=TRUE))
# melting for ggplot
pdata <- reshape2::melt(ddata, id.vars = x_var, variable.name = y_var,
value.name = value_var)
## Set up a blank theme--------------------------------------------------------
theme_none <- function() {
ggplot2::theme(
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_blank(),
axis.title.x = ggplot2::element_text(colour=NA),
axis.title.y = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank(),
axis.line = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank()
)
}
# creating heatmap--------------------------------------------------------------
p_h <- ggplot2::ggplot(pdata, ggplot2::aes_string(x=x_var, y=y_var))
p_hl <- p_h +
ggplot2::geom_tile(ggplot2::aes_string(fill=value_var)) +
ggplot2::scale_fill_gradient2(low = "#9A0038", mid = "#FFFFFF", high = "#003AC3",
midpoint=0,
breaks=c(ceiling(min(pdata[,value_var])), 0,
floor(max(pdata[, value_var]))),
ggplot2::guide_legend(title='Normalized Count')) +
ggplot2::theme(panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.background = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.text.y = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
plot.margin = ggplot2::margin(0,0,0,0, 'cm'),
legend.direction='horizontal')
# remove legend from p_hl
p_h <- p_hl + ggplot2::theme(legend.position='none')
## X axis dendrogram 1----------------------------------------------------------
# calculating plot limits
xlim <- range(c(ggdendro::segment(ddata_x)$x, ggdendro::segment(ddata_x)$xend))
ylim <- range(c(ggdendro::segment(ddata_x)$y, ggdendro::segment(ddata_x)$yend))
x_name <- as.character(ggdendro::label(ddata_x)$label)
name_len <- lapply(x_name, function(x) nchar(x))
name_len <- unlist(name_len)
name_len <- max(name_len)
xadjust <- name_len*0.75
xmin <- floor(xlim[1]) - 0.5
xmax <- ceiling(xlim[2])+ 0.5
xlim <- c(xmin, xmax)
ymin <- floor(ylim[1]) - xadjust
ymax <- ceiling(ylim[2]) + 1
ylim <- c(ymin, ymax)
# plotting x-axis dendrogram
p_x <- ggplot2::ggplot() +
ggplot2::geom_segment(data=ddata_x$segment,
ggplot2::aes(x = x, y = y, xend = xend, yend = yend)) +
ggplot2::geom_text(data=ddata_x$labels, ggplot2::aes(x=x, y=y, label=label),
angle=-90, hjust=0, vjust=0.3) +
ggplot2::scale_x_continuous(expand = c(0, 0), limits=xlim) +
ggplot2::scale_y_continuous(expand = c(0, 0), limits=ylim) +
theme_none() +
ggplot2::theme(plot.margin = ggplot2::unit(c(0,0.2,0,0.5), 'cm')) +#t,r,b,l
ggplot2::labs(x=NULL, y=NULL)
## Y axis dendrogram 2----------------------------------------------------------
# calculating plot limits
xlim <- range(c(ggdendro::segment(ddata_y)$x, ggdendro::segment(ddata_y)$xend))
ylim <- range(c(ggdendro::segment(ddata_y)$y, ggdendro::segment(ddata_y)$yend))
ydata_name <- as.character(ggdendro::label(ddata_y)$label)
name_len <- lapply(ydata_name, function(x) nchar(x))
name_len <- unlist(name_len)
name_len <- max(name_len)
yadjust <- name_len*1.6
xmin <- floor(xlim[1]) - 0.5
xmax <- ceiling(xlim[2]) + 0.5
xlim <- c(xmin, xmax)
ymin <- floor(ylim[1]) - yadjust
ymax <- ceiling(ylim[2])
ylim <- c(ymin, ymax)
# plotting y-axis dendrogram
p_y <- ggplot2::ggplot() +
ggplot2::geom_segment(data=ddata_y$segment,
ggplot2::aes(x = x, y = y, xend = xend, yend = yend)) +
ggplot2::geom_text(data=ddata_y$labels, ggplot2::aes(x=x, y=y, label=label),
hjust=1, vjust=0.5) +
ggplot2::coord_flip() +
ggplot2::scale_x_continuous(expand = c(0, 0), limits=xlim) +
ggplot2::scale_y_continuous(expand = c(0, 0), limits=ylim) +
theme_none() +
ggplot2::theme(plot.margin = ggplot2::unit(c(-0.1,0,0.6,0), 'cm')) +
ggplot2::labs(x=NULL, y=NULL)
# plot caption
x_dist <- x_dist
x_hclust <- x_hclust
y_dist <- y_dist
y_hclust <- y_hclust
caption <- stringr::str_c(sprintf("X-Axis Dendrogram:\n Distance method: %s\n Linkage method: %s\n\n",x_dist, x_hclust),
sprintf("Y-Axis Dendrogram:\n Distance method: %s\n Linkage method: %s", y_dist, y_hclust))
# putting plots together--------------------------------------------------------
# extracting legend
g_hl <- ggplot2::ggplotGrob(p_hl)
legend <- grep("guide", g_hl$layout$name)
g_l <- g_hl[["grobs"]][[legend]]
# putting legend and captions together
g_c <- grid::textGrob(label=caption, x=0.2, y=0.3, just='left')
g_cl <- gridExtra::grid.arrange(g_c, g_l, ncol=1)
# converting plots to grobs
g_h <- ggplot2::ggplotGrob(p_h)
g_x <- ggplot2::ggplotGrob(p_x)
g_y <- ggplot2::ggplotGrob(p_y)
mat <- matrix(list(g_x, g_h, g_cl, g_y), nrow=2)
g <- gtable::gtable_matrix(name='heatmap',grobs=mat,
widths=ggplot2::unit(c(heatmap_w,dendro_y_w),'cm'),
heights=ggplot2::unit(c(dendro_x_h, heatmap_h), 'cm'))
# saving plot
ggplot2::ggsave(out, g, width=(heatmap_w+dendro_y_w)*1.01,
height=(heatmap_h+dendro_x_h)*1.01, unit='cm')
msg <- sprintf("\nSaving heatmap:\n%s", out)
message(msg)
return(list('pdata'=pdata, 'ddata_x'=ddata_x,
'ddata_x'=ddata_x, 'p_hl'=p_hl,'p_x'=p_x,'p_y'=p_y,
'g' = g))
}
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