Any Way to Make Plot Points in Scatterplot More Transparent in R

Any way to make plot points in scatterplot more transparent in R?

Otherwise, you have function alpha in package scales in which you can directly input your vector of colors (even if they are factors as in your example):

library(scales)
cols <- cut(z, 6, labels = c("pink", "red", "yellow", "blue", "green", "purple"))
plot(x, y, main= "Fragment recruitment plot - FR-HIT", 
     ylab = "Percent identity", xlab = "Base pair position", 
     col = alpha(cols, 0.4), pch=16) 
# For an alpha of 0.4, i. e. an opacity of 40%.

R - ggplot - jitter plot with transparent data points

You should be able to use position_jitter in the point geometry. The width and height parameters are the amount of jitter on the x- and y-axes respectively:

p<-ggplot(house_data,aes(x=cloudCover, y=solar_energy, color = day_night)) 
p<-p+geom_point(alpha = 0.01, position=position_jitter(height=.5, width=.5))
p

Control the size of points in an R scatterplot?

Try the cex argument:

?par

• cex
  
  A numerical value giving the
  amount by which plotting text and
  symbols should be magnified relative
  to the default. Note that some
  graphics functions such as
  plot.default have an argument of this
  name which multiplies this graphical
  parameter, and some functions such as
  points accept a vector of values
  which are recycled. Other uses will
  take just the first value if a vector
  of length greater than one is
  supplied.

ggplot XY scatter - how to change alpha transparency for select points?

We can use annotate:

ggplot(df, aes(x=SeqIdentityMean,
               y=SeqIdentityStdDev,
               color=PfamA_ID))+
  geom_point(alpha=0.05) +
  annotate("point",
           df$SeqIdentityMean[special.points],
           df$SeqIdentityStdDev[special.points])

Using @jlhoward's example data:

## create artificial data set for this example
set.seed(1)     # for reproducibility
n  <- 1.4e4     # 14,000 points
df <- data.frame(SeqIdentityMean  =rnorm(n, mean=rep(-3:3, each=n/7)), 
                 SeqIdentityStdDev=rnorm(n, mean=rep(-3:3, each=n/7)),
                 PfamA_ID=rep(1:7, each=n/7))
df$PfamA_ID <- factor(df$PfamA_ID)

## you start here
library(ggplot2)
special.points <- sample(1:n, 7)

---

EDIT 1:
We can add annotate("text",...)

ggplot(df, aes(x=SeqIdentityMean,
               y=SeqIdentityStdDev)) +
  geom_point(alpha=0.05) +
  annotate("point",
           df$SeqIdentityMean[special.points],
           df$SeqIdentityStdDev[special.points],
           col="red") +
  annotate("text",
           df$SeqIdentityMean[special.points],
           df$SeqIdentityStdDev[special.points],
           #text we want to display
           label=round(df$SeqIdentityStdDev[special.points],1),
           #adjust horizontal position of text
           hjust=-0.1)

---

EDIT 2:

#subset of special points
df_sp <- df[special.points,]

#plot
ggplot(df, aes(x=SeqIdentityMean,
               y=SeqIdentityStdDev)) +
  geom_point(alpha=0.05) +
  #special points
  geom_point(data=df_sp,
             aes(SeqIdentityMean,SeqIdentityStdDev,col=PfamA_ID),size=3) +
  #custom legend
  scale_colour_manual(name = "Special Points",
                      values = df_sp$PfamA_ID,
                      labels = df_sp$SeqIdentityMean)

Adding jitter or transparency to points in Highcharter scatter plot in R

What you could do is use states which means that when you highlight one point, the other points opacity will be lower. Here is code:

library(highcharter)
library(tidyverse)

clist %>%
  hchart("scatter", hcaes(x = completion_rate, y = synergy_scores, group = course_code)) %>% 
  hc_xAxis(title = list(text = "Completion rate")) %>%
  hc_yAxis(title = list(text = "Synergy score")) %>% 
  hc_tooltip(pointFormat ="<b> Synergy score: </b> {point.y} <br>") %>% 
  hc_title(text = "Courses with positive and negative Synergy scores") %>%
  hc_plotOptions(series = list(states = list(inactive = list(opacity = 0.5))))

Output:

What you can see is that the other points have lower transparency than the one that is highlighted.

---

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