Layered plotting of selected points in an efficien

Q: Is there any efficient way to plot selected points only after all the remaining points?

Data used for plotting is generated as:

# Loading required libraries
library(ggplot2)
library(forcats)
library(tidyverse)
library(RColorBrewer)

# Data generation process
df <- data.frame(X=rnorm(10000,0,1), Y=rnorm(10000,0,1), 
                 ID=paste(rep("ID", 10000), 1:10000, sep="_"),
                 Type=rep("ID",10000),
                 Val=c(rep(c('Type1','Type2'),3000),
                       rep(c('Type3','Type4'),2000)))

dat1 <- data.frame(Type=rep('CT',80),
                   Val=paste(rep("CT", 80), 
                             sample(1:6,80,replace=T), sep="_"))
dat1 <- cbind(df[sample(1:100,80),1:3],dat1)

dat2 <- data.frame(Type=rep('D',80),
                   Val=paste(rep("D", 80), 
                             sample(1:6,80,replace=T), sep="_"))
dat2 <- cbind(df[sample(1:100,80),1:3],dat2)

dat3 <- data.frame(Type=rep('OP',80),
                   Val=paste(rep("OP", 80), 
                             sample(1:6,80,replace=T), sep="_"))
dat3 <- cbind(df[sample(1:100,80),1:3],dat3)

# Final data
df <- rbind(df, dat1, dat2, dat3)

Plotting the selected values valsToKeep as colored and the rest as hollow circles.

valsToKeep <- c("D_1","D_4")
n <- length(valsToKeep)
getPaletteDark = brewer.pal(8,"Dark2")
colSel <- sample(getPaletteDark,n)

ggplot(df %>% 
         mutate(Val=fct_other(Val,keep=valsToKeep)) %>% 
         arrange(Val) %>% 
         filter(!duplicated(.[,c("X","Y")])), 
       aes(X,Y,col=Val,alpha=Val,shape=Val)) + 
  geom_point(alpha=1) +
  scale_colour_manual(values=c(colSel,"grey70")) +
  scale_alpha_manual(values = c(rep(1,n),0.2)) +
  scale_shape_manual(values = c(rep(16,n),1)) +
  theme_bw()

However, it is very difficult to find the selected values valsToKeep. They are masked by Other points. To find the selected values valsToKeep, the size of the points are increased as suggested here:

ggplot(df %>% 
         mutate(Val=fct_other(Val,keep=valsToKeep)) %>% 
         arrange(Val) %>% 
         filter(!duplicated(.[,c("X","Y")])), 
       aes(X,Y,col=Val,alpha=Val,shape=Val,size=Val)) + 
  geom_point(alpha=1) +
  scale_colour_manual(values=c(colSel,"grey70")) +
  scale_alpha_manual(values = c(rep(1,n),0.2)) +
  scale_shape_manual(values = c(rep(16,n),1)) +
  scale_size_manual(values = c(rep(6,n),1)) +
  theme_bw()

Still the selected points are masked by Other and difficult to identify the patterns behind. Alternatively, tried to plot the plots in multiple layers as below:

dfPlot <- df %>% mutate(Val=fct_other(Val,keep=valsToKeep)) %>% 
  arrange(Val) %>% filter(!duplicated(.[,c("X","Y")]))

p1 <- ggplot(dfPlot %>% filter(Val=='Other'), aes(X,Y)) + 
  geom_point(alpha=0.2,col="grey70",shape=1) + theme_bw() 

p1 + geom_point(data=dfPlot %>% filter(!Val=='Other'),aes(X,Y,col=Val)) + 
  scale_colour_manual(values=colSel)

Now, the plot looks better and easy to identify the patterns of the selected points.

The question is: Is there any other efficient way to plot the selected points (as a second layer) only after plotting the Other points (as a first layer)?

Update:

Here, I have already shown how to plot the selected points in the second layer(using geom_point) on top of already existing first layer (using ggplot() + geom_point). I am looking for alternate approaches available to do that?

The solutions proposed for a similar question are different in this case. Usage of order or alpha do not help in this scenario. So, any alternatives?

Control the alpha and color values manually

# Your data
df <- rbind(df, dat1, dat2, dat3)

Lvls <- sort(unique(df$Val))
Lngth <- length(Lvls)
valstokeep <- c("D_2", "D_4")

# color levels
colormap <- rep("grey", Lngth)
colormap[Lvls %in% valstokeep] <- c("red","blue")

# alpha levels
alphamap <- rep(0.01, Lngth)   # change to lower or higher alpha levels
alphamap[Lvls %in% valstokeep] <- c(1,1)

ggplot(data=df, aes(x=X, y=Y, alpha=Val, color=Val, fill=Val)) +
  geom_point() +
  scale_alpha_manual(values=alphamap) +
  scale_color_manual(values=colormap) + 
  scale_fill_manual(values=colormap) +
  theme_classic()