I have this code for a dendrogram. How can I decrease the size of dendrogram (or y-axis)?
I am using this code as example. In my dataset, I have large labels so I do not have space enough to include it. For that reason, I would like to reduce the space used for y axis, decrease the distance between 0 and 150. Also, when I save the figure as tiff, most of figure is the dendogram and I can not see labels clearly.
df <- USArrests # really bad idea to muck up internal datasets
labs <- paste("sta_",1:50,sep="") # new labels
rownames(df) <- labs # set new row names
library(ggplot2)
library(ggdendro)
hc <- hclust(dist(df), "ave") # heirarchal clustering
dendr <- dendro_data(hc, type="rectangle") # convert for ggplot
clust <- cutree(hc,k=2) # find 2 clusters
clust.df <- data.frame(label=names(clust), cluster=factor(clust))
# dendr[["labels"]] has the labels, merge with clust.df based on label column
dendr[["labels"]] <- merge(dendr[["labels"]],clust.df, by="label")
# plot the dendrogram; note use of color=cluster in geom_text(...)
ggplot() +
geom_segment(data=segment(dendr), aes(x=x, y=y, xend=xend, yend=yend)) +
geom_text(data=label(dendr),
aes(x, y, label=label, hjust=0, color=cluster),
size=3) +
coord_flip() +
scale_y_reverse(expand=c(0.2, 0)) +
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_blank(),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
How can I decrease the size of dendogram similar than this heatmap?
(source: r-graph-gallery.com)
Thanks you so much
For flexibility, I recommend putting the dendrogram labels on the x-axis itself, rather than text labels within the plot. Otherwise no matter what values you choose for expand in the y-axis, part of the labels could be cut off for some image sizes / dimensions.
Define colour palette for the dendrogram labels:
library(dplyr)
label.colour = label(dendr)$cluster %>%
factor(levels = levels(.),
labels = scales::hue_pal()(n_distinct(.))) %>%
as.character()
For the purpose of illustration, make some labels very long:
label.values <- forcats::fct_recode(
label(dendr)$label,
sta_45_abcdefghijklmnop = "sta_45",
sta_31_merrychristmas = "sta_31",
sta_6_9876543210 = "sta_6")
Plot:
p <- ggplot(segment(dendr)) +
geom_segment(aes(x=x, y=y, xend=xend, yend=yend)) +
coord_flip() +
scale_x_continuous(breaks = label(dendr)$x,
# I'm using label.values here because I made
# some long labels for illustration. you can
# simply use `labels = label(dendr)$label`
labels = label.values,
position = "top") +
scale_y_reverse(expand = c(0, 0)) +
theme_minimal() +
theme(axis.title = element_blank(),
axis.text.y = element_text(size = rel(0.9),
color = label.colour),
panel.grid = element_blank())
p
# or if you want a color legend for the clusters
p + geom_point(data = label(dendr),
aes(x = x, y = y, color = cluster), alpha = 0) +
scale_color_discrete(name = "Cluster",
guide = guide_legend(override.aes = list(alpha = 1))) +
theme(legend.position = "bottom")
You can do this by adding a size parameter to axis.text.y like so:
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_text(size=12),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
Related
I'm struggling with a problem:
I created two volcano plots in ggplot2, but due to the fact that I had one outlier point in both plot, I need to add y axis break for better visualization.
The problem arises when I WANT TO plot both in the same page using plot_grid from cowplot::, because it visualizes the original plot without the breaks that I set.
p<- c1 %>%
ggplot(aes(x = avg_log2FC,
y = -log10(p_val_adj),
fill = gene_type,
size = gene_type,
alpha = gene_type)) +
geom_point(shape = 21, # Specify shape and colour as fixed local parameters
colour = "black") +
geom_hline(yintercept = 0,
linetype = "dashed") +
scale_fill_manual(values = cols) +
scale_size_manual(values = sizes) +
scale_alpha_manual(values = alphas) +
scale_x_continuous(limits=c(-1.5,1.5), breaks=seq(-1.5,1.5,0.5)) +
scale_y_continuous(limits=c(0,110),breaks=seq(0,110,25))+
labs(title = "Gene expression",
x = "log2(fold change)",
y = "-log10(adjusted P-value)",
colour = "Expression \nchange") +
theme_bw() + # Select theme with a white background
theme(panel.border = element_rect(colour = "black", fill = NA, size= 0.5),
panel.grid.minor = element_blank(),
panel.grid.major = element_blank())
p1 <- p + scale_y_break(breaks = c(30, 100))
p1
p plot without breaks:
and p1 plot with breaks:
The same I did for the second plot. But this is the result using plot_grid(p1,p3, ncol = 2)
Can you help me understanding if I'm doing something wrong? or it is just a limitation of the package?
OP, it seems in that ggbreak is not compatible with functions that arrange multiple plots, as indicated in the documentation for the package here. There does seem to be a workaround via either print() (I didn't get this to work) or aplot::plot_list(...), which did work for me. Here's an example using built-in datasets.
# setting up the plots
library(ggplot2)
library(ggbreak)
library(cowplot)
p1 <-
ggplot(mtcars, aes(x=mpg, disp)) + geom_point() +
scale_y_break(c(200, 220))
p2 <-
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width, color=Species)) +
geom_point() + scale_y_break(c(3.5, 3.7))
Plots p1 and p2 yield breaks in the y axis like you would expect, but plot_grid(p1,p2) results in the plots placed side-by-side without the y axis breaks.
The following does work to arrange the plots without disturbing the y axis breaks:
aplot::plot_list(p1,p2)
A while ago I asked this question about how to replace a barplots x-axis labels with individual plots and I received an answer. However, I'm back trying to do this again, except this time I want to flip the barplot. The issue I'm having is I cant figure out how to adapt the code in the previous answer to allow me to flip the plot.
For example, if I create some data and a barplot with the x-axis labels replaced by plots like so:
df <- data.frame(vals = c(10, 5, 18),
name = c("A", "B", "C"))
bp <- df %>%
ggplot() +
geom_bar(aes(x = name, y = vals), stat = "identity") +
xlab("") +
theme_bw() +
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank())
# create plots to use as x-axis --------------------------------------------
p1 <- ggplot(df, aes(x = vals, y = vals)) + geom_point() + theme_bw() +
theme(axis.title.x = element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank())
p3 <- p2 <- p1
# turn into list of plots
myList <- list(p1, p2, p3)
# -------------------------------------------------------------------------
# attach plots to axis
width <- .9 # Default width of bars
p_axis <- ggplot(df) +
geom_blank(aes(x = name)) +
purrr::map2(myList, seq_along(myList), ~ annotation_custom(ggplotGrob(.x), xmin = .y - width / 2, xmax = .y + width / 2)) +
theme_void()
bp / p_axis + plot_layout(heights = c(4, 1))
That creates this:
Now, if I add in the line bp + coordflip() while creating the barplot and continue with the rest of the code, the barplot is flipped, but the individual plots remain in place, like so:
I'm guessing I need to alter the p_axis part of the code to fix the individual plots where A, B, C are shown in the above plot... but im not sure exactly what to do to fix this? I tried experimenting but have been unsuccessful so far.
I just changed in annotation_custom the xmin and xmam to ymin and ymax. Also, I changed the part bp / p_axis to p_axis|bp.
p_axis <- ggplot(df) +
geom_blank(aes(y = name)) +
purrr::map2(myList, seq_along(myList), ~ annotation_custom(ggplotGrob(.x), ymin = .y - width / 2, ymax = .y + width / 2)) +
theme_void()
p_axis|bp
Some fine-tuning of the widths are needed. Here is what it looks like now.
A simpler approach at this point is to use the ggExtra package, which has a function ggMarginal() that adds these plots with your choice of geom.
See https://geeksforgeeks.org/r-ggplot2-marginal-plots/ for a nice demonstration
I am attempting to make publication ready figures where the bottom axis (with tick marks) of one figure is cleanly combined with the top axis of the figure below it. Here is an example of what it might look like, although this one doesn't have tick marks on each panel:
Here is my attempt to do so, by simply using grid.arrange:
#Libraries:
library(ggplot2)
library(dplyr)
library(gridExtra)
#Filter to create two separate data sets:
dna1 <- DNase %>% filter(Run == 1)
dna2 <- DNase %>% filter(Run == 2)
#Figure 1:
dna1_plot <- ggplot(dna1, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(axis.title.x = element_blank())
#Figure 2:
dna2_plot <- ggplot(dna2, aes(x = conc, y = density)) + geom_point() + theme_classic()
#Using grid.arrange to combine:
dna <- grid.arrange(dna1_plot, dna2_plot, nrow = 2)
And an attempt with some adjustments to the plot margins, although this didn't seem to work:
dna1_plot_round2 <- ggplot(dna1, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(axis.title.x = element_blank(),
plot.margin = (0,0,0,0), "cm")
dna2_plot_round2 <- ggplot(dna2, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(plot.margin = unit(c(-0.5,-1,0,0), "cm"))
dna_round2 <- grid.arrange(dna1_plot_round2, dna2_plot_round2, nrow = 2)
Does anyone know the best way to stack figures like this in ggplot? Is there a better way than using grid.arrange? If possible it would be great to see how to do it with/without tick marks on each x axis as well.
Thank you!
You don't need any non-native ggplot stuff. Keep your data in one data frame and use facet_grid.
dna <- DNase %>% filter(Run %in% 1:2)
ggplot(dna, aes(x = conc, y = density)) +
geom_point() +
theme_bw() +
facet_grid(rows = vars(Run)) +
theme(panel.spacing = unit(0, "mm"))
The R package deeptime has a function called ggarrange2 that can achieve this. Instead of just pasting the plots together like grid.arrange (and ggarrange), it lines up all of the axes and axis labels from all of the plots.
# remove bottom axis elements, reduce bottom margin, add panel border
dna1_plot_round2 <- ggplot(dna1, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank(),
plot.margin = margin(0,0,-.05,0, "cm"), panel.border = element_rect(fill = NA))
# reduce top margin (split the difference so the plots are the same height), add panel border
dna2_plot_round2 <- ggplot(dna2, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(plot.margin = margin(-.05,0,0,0, "cm"), panel.border = element_rect(fill = NA))
dna_round2 <- ggarrange2(dna1_plot_round2, dna2_plot_round2, nrow = 2)
You might also try the fairly recent patchwork package, although I don't have much experience with it.
Note that while Gregor's answer may be fine for this specific example, this answer might be more appropriate for other folks that come across this question (and see the example at the top of the question).
For your purposes, I believe Gregor Thomas' answer is best. But if you are in a situation where facets aren't the best option for combining two plots, the newish package {{patchwork}} handles this more elegantly than any alternatives I've seen.
Patchwork also provides lots of options for adding annotations surrounding the combined plot. The readME and vignettes will get you started.
library(patchwork)
(dna1_plot / dna2_plot) +
plot_annotation(title = "Main title for combined plots")
Edit to better address #Cameron's question.
According to the package creator, {{patchwork}} does not add any space between the plots. The white space in the example above is due to the margins around each individual ggplot. These margins can be adjusted using the plot.margin argument in theme(), which takes a numeric vector of the top, right, bottom, and left margins.
In the example below, I set the bottom margin of dna1_plot to 0 and strip out all the bottom x-axis ticks and text. I also set the top margin of dna2_plot to 0. Doing this nearly makes the y-axis lines touch in the two plots.
dna1_plot <- ggplot(dna1, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(axis.title.x = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank(),
plot.margin = unit(c(1,1,0,1), "mm"))
#Figure 2:
dna2_plot <- ggplot(dna2, aes(x = conc, y = density)) + geom_point() + theme_classic() +
theme(plot.margin = unit(c(0,1,1,1), "mm"))
(dna1_plot / dna2_plot)
I am trying to display color gradient in below created ggplot2. So with using following data and code
vector <- c(9, 10, 6, 5, 5)
Names <- c("Leadership", "Management\n", "Problem Solving",
"Decision Making\n", "Social Skills")
# add \n
Names[seq(2, length(Names), 2)] <- paste0("\n" ,Names[seq(2, length(Names), 2)])
# data.frame, including a grouping vector
d <- data.frame(Names, vector, group=c(rep("Intra-capacity", 3), rep("Inter-capacity", 2)))
# correct order
d$Names <- factor(d$Names, levels= unique(d$Names))
d$group_f = factor(d$group, levels=c('Intra-capacity','Inter-capacity'))
# plot the bars
p <- ggplot(d, aes(x= Names, y= vector, group= group, fill=vector, order=vector)) +
geom_bar(stat= "identity") +
theme_bw()+
scale_fill_gradient(low="white",high="blue")
# use facet_grid for the groups
#p + facet_grid(.~group_f, scales= "free_x", space= "free_x")
p+ theme(text = element_text(size=23),plot.background = element_rect(fill = "white"),
strip.background = element_rect(fill="Dodger Blue")) +
facet_grid(.~group_f, scales= "free_x", space= "free_x") + xlab("") +ylab("") +
theme(strip.text.x = element_text(size = 18, colour = "white" )) +
geom_text(size=10, aes(label=vector))
My output is this:
But now I would like to insert color gradient so each rectangle would look like picture below (my desired output):
I've also looked at this:
R: gradient fill for geom_rect in ggplot2
create an arrow with gradient color
http://www.computerworld.com/article/2935394/business-intelligence/my-ggplot2-cheat-sheet-search-by-task.html
Color Gradients With ggplot
Label minimum and maximum of scale fill gradient legend with text: ggplot2
How can I apply a gradient fill to a geom_rect object in ggplot2?
And also tried using:
scale_fill_gradient(low="white",high="blue") or
scale_fill_gradientn(colours = c("blue","white","red"),
values = c(0,5,10),
guide = "colorbar", limits=c(0,10))
But I am clearly doing something wrong.
I'm with #RomanLustrik here. However, if you can't use Excel (= prly much easier), maybe just adding a white rectangle with an alpha-gradient is already enough:
ggplot(d, aes(x= Names, y= vector, group= group,order=vector)) +
geom_bar(stat= "identity", fill="blue") +
theme_bw() +
scale_fill_gradient(low="white",high="blue") +
annotation_custom(
grid::rasterGrob(paste0("#FFFFFF", as.hexmode(1:255)),
width=unit(1,"npc"),
height = unit(1,"npc"),
interpolate = TRUE),
xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=5
) +
geom_text(aes(label=vector), color="white", y=2, size=12)
I have been using the plot_grid command from cowplot to arrange my plots. I use the labeling feature, and my plots all look the same in that regard. However, when I 'hv' align some plots that have very different y-axis limits, such as the one below, it appears the height of the plot with shortest range of y is used.
If I just 'v' align the plot it looks better in some respects, but it is hard to resize the plot and have the labels looking good. I'd prefer the plot height not consider the x-axis labels, etc, like above.
Using gtables, I can get the desired width/height (below), but these leaves me without the consistent labels across all the figures in a document. Can I use the 'hv' alignment with cowplot and specify which plot height to use?
library(ggplot2)
library(dplyr)
library(scales)
library(grid)
library(cowplot)
data(iris)
iris <- iris %>% mutate(Petal.Width2 = ifelse(Species == "setosa", Petal.Width * 75, Petal.Width))
p1 <- ggplot(data=iris, aes(x = factor(Species), y=Sepal.Width)) +
geom_bar(stat="identity") +
labs(x = NULL, y = "Plot One") +
scale_y_continuous(labels = percent) +
theme(axis.text.x = element_blank(),
axis.title.y = element_text(vjust=1), plot.margin=unit(c(2,2,0,2),"mm"))
p2 <- ggplot(data=iris, aes(x = factor(Species), y=Petal.Width2)) + geom_bar(stat="identity") +
labs(x = NULL, y = "Plot Two") +
scale_y_continuous(labels = percent) +
theme(axis.text.x = element_blank(),
axis.title.y = element_text(vjust=1), plot.margin=unit(c(0,2,0,2),"mm"))
p3 <- ggplot(data=iris, aes(x = factor(Species), y=Petal.Length*0+.01)) + geom_bar(stat="identity") +
labs(x = "SPECIES", y = "The Third plot") +
scale_y_continuous(labels = percent) +
theme( axis.title.y = element_text(vjust=1, color="blue"), plot.margin=unit(c(0,2,0,2),"mm"),
axis.text.x = element_text(angle = 90, hjust=1, vjust=1,face ="italic", size=10))
plot_grid(p1,p2,p3,ncol=1, align="v", labels=c("A", "B", "C"))
# https://stackoverflow.com/a/27408589/1670053
plots <- list(p1, p2, p3)
grobs = lapply(plots, ggplotGrob)
g = do.call(rbind, c(grobs, size="first"))
g$widths = do.call(unit.pmax, lapply(grobs, "[[", "widths"))
grid.newpage()
grid.draw(g)
it's easy as to add labels,
plots <- list(p1, p2, p3)
grobs = lapply(plots, ggplotGrob)
library(gridExtra)
g = do.call(rbind, grobs) # uses gridExtra::rbind.gtable
panels <- g$layout[g$layout$name=="panel",]
g <- gtable::gtable_add_grob(g, lapply(LETTERS[1:nrow(panels)],
textGrob, vjust=1, y=1,
gp=gpar(fontface=2)),
t=panels$t, l=2)
grid.newpage()
grid.draw(g)