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I'm new to flowCore + R. I would like to mimic a histogram plot after gating that can be manually done in FlowJo software. I got something similar but it doesn't look quite right because it is a "density" plot and is shifted. How can I get the x axis to shift over and look similar to how FlowJo outputs the plot? I tried reading this document but couldn't find a plot similar to the one in FlowJo: howtoflowcore Appreciate any guidance. Thanks.
code snippet:
library(flowCore)
parentpath <- "/parent/path"
subfolder <- "Sample 1"
fcs_files <- list.files(paste0(parentpath, subfolder), pattern = ".fcs")
fs <- read.flowSet(fcs_files)
rect.g <- rectangleGate(filterId = "main",list("FSC-A" = c(1e5, 2e5), "SSC-A" = c(3e4,1e5)))
fs_sub <- Subset(fs, rect.g)
p <- ggcyto(fs_sub[[15]], aes(x= `UV-379-A`)) +
geom_density(fill='black', alpha = 0.4) +
ggcyto_par_set(limits = list(x = c(-1e3, 5e4), y = c(0, 6e-5)))
p
FlowJo output:
R FlowCore output:
The reason that for the "shift" is that the x axis is logarithmic (base 10) in the flowJo graph. To achieve the same result in R, add
+ scale_x_log10()
after the existing code. This might interact weirdly with the axis limits you've set, so bare that in mind.
To make the y-axis "count" rather than density, you can change the first line of your ggcyto() call to:
aes(x= `UV-379-A`, y = after_stat(count))
Let me know if that works - I don't have your data to hand so that's all from memory!
For any purely aesthetic changes, they are relatively easy to look up.
I'd like to create a subtitle with a few custom colored words in ggplot2. We can use crayon::make_style, glue::glue, and glue::glue_col to make this happen in the console (see below). However, when implementing in the graphics device, the color doesn't render. I looked through the source code for a hint but failed to find one. Any thoughts?
library(glue)
library(crayon)
library(tidyverse)
# create data frame
myDat <- tibble(alpha = rnorm(50),
omega = runif(50))
# use crayon to create our custom colors
slate_g <- crayon::make_style("slategrey")
light_s <- make_style("lightsalmon")
# create custom subtitle NOTE it prints cleanly in the console
cust_subt <- glue("
{str_wrap(\"It is a wonder that this subtitle is so dangerously long. Good thing we can wrap it in glue.\", 75)}
Really makes me wonder
{glue_col(\'{bold({slate_g(\"NEVER\")})} vs. {bold({light_s(\"ENOUGH\")})}\')}
")
Here is how the cust_subt object prints in the console.
Once we try to plot, though, it fails.
# custom subtitle DOES NOT work in subtitle
ggplot(myDat, aes(alpha, omega)) +
geom_point() +
labs(subtitle = cust_subt)
#### regular glue works just fine though
cust_subt_no_col <- glue("
{str_wrap(\"It is a wonder that this subtitle is so dangerously long. Good thing we can wrap it in glue.\", 75)}
Really makes me wonder
")
ggplot(myDat, aes(alpha, omega)) +
geom_point() +
labs(subtitle = cust_subt_no_col)
I tried to use the plotly package, but it is not working in my case at all. The ggplot package is working for 2D plots but it is giving an error when adding one more axis. How to solve this issue?
ggplot(data,aes(x=D1,y=D2,z=D3,color=Sample)) +
geom_point()
How to add one more axis and get the 3D plot in this?
Since you tagged your question with plotly and said that you've tried to use it with plotly, I think it would be helpful to give you a working code solution in plotly:
Creating some data to plot with:
set.seed(417)
library(plotly)
temp <- rnorm(100, mean=30, sd=5)
pressure <- rnorm(100)
dtime <- 1:100
Graphing your 3d scatterplot using plotly's scatter3d type:
plot_ly(x=temp, y=pressure, z=dtime, type="scatter3d", mode="markers", color=temp)
Renders the following:
ggplot as others have note, by itself does not support 3d graphics rendering.
A possible solutions is gg3D.
gg3D is a package created to extend ggplot2 to produce 3D plots. It does exactly what you are asking for: it adds a third axis to a ggplot. I find it quite good and easy to use and that is what I use for my limited needs.
An example taken from the vignette to produce a basic plot
devtools::install_github("AckerDWM/gg3D")
library("gg3D")
## An empty plot with 3 axes
qplot(x=0, y=0, z=0, geom="blank") +
theme_void() +
axes_3D()
## Axes can be populated with points using the function stat_3D.
data(iris)
ggplot(iris, aes(x=Petal.Width, y=Sepal.Width, z=Petal.Length, color=Species)) +
theme_void() +
axes_3D() +
stat_3D()
There are other options not involving ggplot. For example the excellent plot3D package with its extension plot3Drgl to plot in openGL.
In your question, you refer to the plotly package and to the ggplot2 package. Both plotly and ggplot2 are great packages: plotly is good at creating dynamic plots that users can interact with, while ggplot2 is good at creating static plots for extreme customization and scientific publication. It is also possible to send ggplot2 output to plotly. Unfortunately, at the time of writing (April 2021), ggplot2 does not natively support 3d plots. However, there are other packages that can be used to produce 3d plots and some ways to get pretty close to ggplot2 quality. Below I review several options. These suggestions are by no means exhaustive.
plotly
See onlyphantom's answer in this thread.
gg3D
See Marco Stamazza's answer in this thread. See also my effort below.
scatterplot3d
See Seth's answer in a related thread.
lattice
See Backlin's answer in a related thread.
rgl
See this overview in the wiki guide.
rayshader
See this overview of this package's wonderful capabilities.
trans3d
See data-imaginist use trans3d to get a cube into ggplot2.
ggrgl
See this cool and useful coolbutuseless introduction.
Now let me review some of my efforts with the Lorenz attractor trajectories. While customization remains limited, I've had best results for PDF output with gg3D. I also include a ggrgl example.
gg3D
# Packages
library(deSolve)
library(ggplot2)
library(gg3D) # remotes::install_github("AckerDWM/gg3D")
# Directory
setwd("~/R/workspace/")
# Parameters
parms <- c(a=10, b=8/3, c=28)
# Initial state
state <- c(x=0.01, y=0.0, z=0.0)
# Time span
times <- seq(0, 50, by=1/200)
# Lorenz system
lorenz <- function(times, state, parms) {
with(as.list(c(state, parms)), {
dxdt <- a*(y-x)
dydt <- x*(c-z)-y
dzdt <- x*y-b*z
return(list(c(dxdt, dydt, dzdt)))
})
}
# Make dataframe
df <- as.data.frame(ode(func=lorenz, y=state, parms=parms, times=times))
# Make plot
make_plot <- function(theta=0, phi=0){
ggplot(df, aes(x=x, y=y, z=z, colour=time)) +
axes_3D(theta=theta, phi=phi) +
stat_3D(theta=theta, phi=phi, geom="path") +
labs_3D(theta=theta, phi=phi,
labs=c("x", "y", "z"),
angle=c(0,0,0),
hjust=c(0,2,2),
vjust=c(2,2,-2)) +
ggtitle("Lorenz butterfly") +
theme_void() +
theme(legend.position = "none")
}
make_plot()
make_plot(theta=180,phi=0)
# Save plot as PDF
ggsave(last_plot(), filename="lorenz-gg3d.pdf")
Pros: Outputs high-quality PDF:
Cons: Still limited customization. But for my specific needs, currently the best option.
ggrgl
# Packages
library(deSolve)
library(ggplot2)
library(rgl)
#remotes::install_github("dmurdoch/rgl")
library(ggrgl)
# remotes::install_github('coolbutuseless/ggrgl', ref='main')
library(devout)
library(devoutrgl)
# remotes::install_github('coolbutuseless/devoutrgl', ref='main')
library(webshot2)
# remotes::install_github("rstudio/webshot2")
library(ggthemes)
# Directory
setwd("~/R/workspace/")
# Parameters
parms <- c(a=10, b=8/3, c=26.48)
# Initial state
state <- c(x=0.01, y=0.0, z=0.0)
# Time span
times <- seq(0, 100, by=1/500)
# Lorenz system
lorenz <- function(times, state, parms) {
with(as.list(c(state, parms)), {
dxdt <- a*(y-x)
dydt <- x*(c-z)-y
dzdt <- x*y-b*z
return(list(c(dxdt, dydt, dzdt)))
})
}
# Make dataframe
df <- as.data.frame(ode(func=lorenz, y=state, parms=parms, times=times))
# Make plot
ggplot(df, aes(x=x, y=y, z=z)) +
geom_path_3d() +
ggtitle("Lorenz butterfly") -> p
# Render Plot in window
rgldev(fov=30, view_angle=-10, zoom=0.7)
p + theme_ggrgl(16)
# Save plot as PNG
rgldev(fov=30, view_angle=-10, zoom=0.7,
file = "~/R/Work/plots/lorenz-attractor/ggrgl/lorenz-ggrgl.png",
close_window = TRUE, dpi = 300)
p + theme_ggrgl(16)
dev.off()
Pros: The plot can be rotated in a way similar to plotly. It is possible to 'theme' a basic plot:
Cons: The figure is missing a third axis with labels. Cannot output high-quality plots. While I've been able to view and save a low-quality black trajectory in PNG, I could view a colored trajectory like the above, but could not save it, except with a low-quality screenshot:
Related threads: plot-3d-data-in-r, ploting-3d-graphics-with-r.
I would like to add LaTeX typesetting to elements of plots in R (e.g: the title, axis labels, annotations, etc.) using either the combination of base/lattice or with ggplot2.
Questions:
Is there a way to get LaTeX into plots using these packages, and if so, how is it done?
If not, are there additional packages needed to accomplish this.
For example, in Python matplotlib compiles LaTeX via the text.usetex packages as discussed here: http://www.scipy.org/Cookbook/Matplotlib/UsingTex
Is there a similar process by which such plots can be generated in R?
The CRAN package latex2exp contains a TeX function that translate LaTeX formulas to R's plotmath expressions. You can use it anywhere you could enter mathematical annotations, such as axis labels, legend labels, and general text.
For example:
x <- seq(0, 4, length.out=100)
alpha <- 1:5
plot(x, xlim=c(0, 4), ylim=c(0, 10),
xlab='x', ylab=TeX(r'($\alpha x^\alpha$, where $\alpha \in \{1 \ldots 5\}$)'),
type='n', main=TeX(r'(Using $\LaTeX$ for plotting in base graphics!)', bold=TRUE))
for (a in alpha) {
lines(x, a*x^a, col=a)
}
legend('topleft',
legend=TeX(sprintf(r'($\alpha = %d$)', alpha)),
lwd=1,
col=alpha)
produces this plot.
Here's an example using ggplot2:
q <- qplot(cty, hwy, data = mpg, colour = displ)
q + xlab(expression(beta +frac(miles, gallon)))
As stolen from here, the following command correctly uses LaTeX to draw the title:
plot(1, main=expression(beta[1]))
See ?plotmath for more details.
You can generate tikz code from R:
http://r-forge.r-project.org/projects/tikzdevice/
Here's something from my own Lab Reports.
tickzDevice exports tikz images for LaTeX
Note, that in certain cases "\\" becomes "\" and "$" becomes "$\" as in the following R code: "$z\\frac{a}{b}$" -> "$\z\frac{a}{b}$\"
Also xtable exports tables to latex code
The code:
library(reshape2)
library(plyr)
library(ggplot2)
library(systemfit)
library(xtable)
require(graphics)
require(tikzDevice)
setwd("~/DataFolder/")
Lab5p9 <- read.csv (file="~/DataFolder/Lab5part9.csv", comment.char="#")
AR <- subset(Lab5p9,Region == "Forward.Active")
# make sure the data names aren't already in latex format, it interferes with the ggplot ~ # tikzDecice combo
colnames(AR) <- c("$V_{BB}[V]$", "$V_{RB}[V]$" , "$V_{RC}[V]$" , "$I_B[\\mu A]$" , "IC" , "$V_{BE}[V]$" , "$V_{CE}[V]$" , "beta" , "$I_E[mA]$")
# make sure the working directory is where you want your tikz file to go
setwd("~/TexImageFolder/")
# export plot as a .tex file in the tikz format
tikz('betaplot.tex', width = 6,height = 3.5,pointsize = 12) #define plot name size and font size
#define plot margin widths
par(mar=c(3,5,3,5)) # The syntax is mar=c(bottom, left, top, right).
ggplot(AR, aes(x=IC, y=beta)) + # define data set
geom_point(colour="#000000",size=1.5) + # use points
geom_smooth(method=loess,span=2) + # use smooth
theme_bw() + # no grey background
xlab("$I_C[mA]$") + # x axis label in latex format
ylab ("$\\beta$") + # y axis label in latex format
theme(axis.title.y=element_text(angle=0)) + # rotate y axis label
theme(axis.title.x=element_text(vjust=-0.5)) + # adjust x axis label down
theme(axis.title.y=element_text(hjust=-0.5)) + # adjust y axis lable left
theme(panel.grid.major=element_line(colour="grey80", size=0.5)) +# major grid color
theme(panel.grid.minor=element_line(colour="grey95", size=0.4)) +# minor grid color
scale_x_continuous(minor_breaks=seq(0,9.5,by=0.5)) +# adjust x minor grid spacing
scale_y_continuous(minor_breaks=seq(170,185,by=0.5)) + # adjust y minor grid spacing
theme(panel.border=element_rect(colour="black",size=.75))# border color and size
dev.off() # export file and exit tikzDevice function
Here's a cool function that lets you use the plotmath functionality, but with the expressions stored as objects of the character mode. This lets you manipulate them programmatically using paste or regular expression functions. I don't use ggplot, but it should work there as well:
express <- function(char.expressions){
return(parse(text=paste(char.expressions,collapse=";")))
}
par(mar=c(6,6,1,1))
plot(0,0,xlim=sym(),ylim=sym(),xaxt="n",yaxt="n",mgp=c(4,0.2,0),
xlab="axis(1,(-9:9)/10,tick.labels,las=2,cex.axis=0.8)",
ylab="axis(2,(-9:9)/10,express(tick.labels),las=1,cex.axis=0.8)")
tick.labels <- paste("x >=",(-9:9)/10)
# this is what you get if you just use tick.labels the regular way:
axis(1,(-9:9)/10,tick.labels,las=2,cex.axis=0.8)
# but if you express() them... voila!
axis(2,(-9:9)/10,express(tick.labels),las=1,cex.axis=0.8)
I did this a few years ago by outputting to a .fig format instead of directly to a .pdf; you write the titles including the latex code and use fig2ps or fig2pdf to create the final graphic file. The setup I had to do this broke with R 2.5; if I had to do it again I'd look into tikz instead, but am including this here anyway as another potential option.
My notes on how I did it using Sweave are here: http://www.stat.umn.edu/~arendahl/computing
I just have a workaround. One may first generate an eps file, then convert it back to pgf using the tool eps2pgf. See http://www.texample.net/tikz/examples/eps2pgf/
h <- rnorm(mean = 5, sd = 1, n = 1000)
hist(h, main = expression(paste("Sampled values, ", mu, "=5, ", sigma,
"=1")))
Taken from a very help article here https://stats.idre.ucla.edu/r/codefragments/greek_letters/
You can use the following, for example:
title(sub=TeX(sprintf(paste("Some latex symbols are ", r'(\lambda)', "and", r'(\alpha)'))))
Just remember to enclose LaTeX expressions in paste() using r'()'
You can also add named objects in the paste() function. E.g.,
lambda_variable <- 3
title(sub=TeX(sprintf(paste(r'(\lambda=)', lambda_variable))))
Not sure if there are better ways to do this, but the above worked for me :)
I would like to add LaTeX typesetting to elements of plots in R (e.g: the title, axis labels, annotations, etc.) using either the combination of base/lattice or with ggplot2.
Questions:
Is there a way to get LaTeX into plots using these packages, and if so, how is it done?
If not, are there additional packages needed to accomplish this.
For example, in Python matplotlib compiles LaTeX via the text.usetex packages as discussed here: http://www.scipy.org/Cookbook/Matplotlib/UsingTex
Is there a similar process by which such plots can be generated in R?
The CRAN package latex2exp contains a TeX function that translate LaTeX formulas to R's plotmath expressions. You can use it anywhere you could enter mathematical annotations, such as axis labels, legend labels, and general text.
For example:
x <- seq(0, 4, length.out=100)
alpha <- 1:5
plot(x, xlim=c(0, 4), ylim=c(0, 10),
xlab='x', ylab=TeX(r'($\alpha x^\alpha$, where $\alpha \in \{1 \ldots 5\}$)'),
type='n', main=TeX(r'(Using $\LaTeX$ for plotting in base graphics!)', bold=TRUE))
for (a in alpha) {
lines(x, a*x^a, col=a)
}
legend('topleft',
legend=TeX(sprintf(r'($\alpha = %d$)', alpha)),
lwd=1,
col=alpha)
produces this plot.
Here's an example using ggplot2:
q <- qplot(cty, hwy, data = mpg, colour = displ)
q + xlab(expression(beta +frac(miles, gallon)))
As stolen from here, the following command correctly uses LaTeX to draw the title:
plot(1, main=expression(beta[1]))
See ?plotmath for more details.
You can generate tikz code from R:
http://r-forge.r-project.org/projects/tikzdevice/
Here's something from my own Lab Reports.
tickzDevice exports tikz images for LaTeX
Note, that in certain cases "\\" becomes "\" and "$" becomes "$\" as in the following R code: "$z\\frac{a}{b}$" -> "$\z\frac{a}{b}$\"
Also xtable exports tables to latex code
The code:
library(reshape2)
library(plyr)
library(ggplot2)
library(systemfit)
library(xtable)
require(graphics)
require(tikzDevice)
setwd("~/DataFolder/")
Lab5p9 <- read.csv (file="~/DataFolder/Lab5part9.csv", comment.char="#")
AR <- subset(Lab5p9,Region == "Forward.Active")
# make sure the data names aren't already in latex format, it interferes with the ggplot ~ # tikzDecice combo
colnames(AR) <- c("$V_{BB}[V]$", "$V_{RB}[V]$" , "$V_{RC}[V]$" , "$I_B[\\mu A]$" , "IC" , "$V_{BE}[V]$" , "$V_{CE}[V]$" , "beta" , "$I_E[mA]$")
# make sure the working directory is where you want your tikz file to go
setwd("~/TexImageFolder/")
# export plot as a .tex file in the tikz format
tikz('betaplot.tex', width = 6,height = 3.5,pointsize = 12) #define plot name size and font size
#define plot margin widths
par(mar=c(3,5,3,5)) # The syntax is mar=c(bottom, left, top, right).
ggplot(AR, aes(x=IC, y=beta)) + # define data set
geom_point(colour="#000000",size=1.5) + # use points
geom_smooth(method=loess,span=2) + # use smooth
theme_bw() + # no grey background
xlab("$I_C[mA]$") + # x axis label in latex format
ylab ("$\\beta$") + # y axis label in latex format
theme(axis.title.y=element_text(angle=0)) + # rotate y axis label
theme(axis.title.x=element_text(vjust=-0.5)) + # adjust x axis label down
theme(axis.title.y=element_text(hjust=-0.5)) + # adjust y axis lable left
theme(panel.grid.major=element_line(colour="grey80", size=0.5)) +# major grid color
theme(panel.grid.minor=element_line(colour="grey95", size=0.4)) +# minor grid color
scale_x_continuous(minor_breaks=seq(0,9.5,by=0.5)) +# adjust x minor grid spacing
scale_y_continuous(minor_breaks=seq(170,185,by=0.5)) + # adjust y minor grid spacing
theme(panel.border=element_rect(colour="black",size=.75))# border color and size
dev.off() # export file and exit tikzDevice function
Here's a cool function that lets you use the plotmath functionality, but with the expressions stored as objects of the character mode. This lets you manipulate them programmatically using paste or regular expression functions. I don't use ggplot, but it should work there as well:
express <- function(char.expressions){
return(parse(text=paste(char.expressions,collapse=";")))
}
par(mar=c(6,6,1,1))
plot(0,0,xlim=sym(),ylim=sym(),xaxt="n",yaxt="n",mgp=c(4,0.2,0),
xlab="axis(1,(-9:9)/10,tick.labels,las=2,cex.axis=0.8)",
ylab="axis(2,(-9:9)/10,express(tick.labels),las=1,cex.axis=0.8)")
tick.labels <- paste("x >=",(-9:9)/10)
# this is what you get if you just use tick.labels the regular way:
axis(1,(-9:9)/10,tick.labels,las=2,cex.axis=0.8)
# but if you express() them... voila!
axis(2,(-9:9)/10,express(tick.labels),las=1,cex.axis=0.8)
I did this a few years ago by outputting to a .fig format instead of directly to a .pdf; you write the titles including the latex code and use fig2ps or fig2pdf to create the final graphic file. The setup I had to do this broke with R 2.5; if I had to do it again I'd look into tikz instead, but am including this here anyway as another potential option.
My notes on how I did it using Sweave are here: http://www.stat.umn.edu/~arendahl/computing
I just have a workaround. One may first generate an eps file, then convert it back to pgf using the tool eps2pgf. See http://www.texample.net/tikz/examples/eps2pgf/
h <- rnorm(mean = 5, sd = 1, n = 1000)
hist(h, main = expression(paste("Sampled values, ", mu, "=5, ", sigma,
"=1")))
Taken from a very help article here https://stats.idre.ucla.edu/r/codefragments/greek_letters/
You can use the following, for example:
title(sub=TeX(sprintf(paste("Some latex symbols are ", r'(\lambda)', "and", r'(\alpha)'))))
Just remember to enclose LaTeX expressions in paste() using r'()'
You can also add named objects in the paste() function. E.g.,
lambda_variable <- 3
title(sub=TeX(sprintf(paste(r'(\lambda=)', lambda_variable))))
Not sure if there are better ways to do this, but the above worked for me :)