Color coding in ggplot using geome_point, while maintaining size of point-CodePudding

This post is hidden. You deleted this post just now. I am plotting a dataset in R using three different variables (x=PassingFilerReads, y=meanCoverage, and size distribution of alignPercentageR1 over those two things), and I am looking to better visualize size the size distribution of align percentage.

right now I am able to see my graph with good layout when I use this code.

ggplot(L2NEW,aes(x=PassingFilterReads,y=meanCoverageP)) 
  geom_point(aes(size=alignPercentR1))   
  ylim(0,60)   
  xlim(0,1500000000)  
  geom_hline(yintercept=30,
             color = "red", 
             linetype="dashed")

How can I edit this so that I can have geom_point(aes(size=alignPercentR1)) also include color? Like alignPercentR1>75= "red", and Like alignPercentR1<75= "blue", and Like alignPercentR1<25= "green"

I have tried a few other ways of adding this to my code, but none have worked how I was hoping.

ggplot(L2NEW,aes(x=PassingFilterReads,y=meanCoverageP)) 
  geom_point(aes(data=L2NEW$alignPercentR1,   
                 color='cyan',
                 size=alignpercentR1>75))   
  ylim(0,70)   
  xlim(0,1500000000)  
  geom_hline(yintercept=30,
             color = "red", 
             linetype="dashed")

Warning: Ignoring unknown aesthetics: data Error in FUN(X[[i]], ...) : object 'alignpercentR1' not found

and

ggplot(L2NEW,aes(x=PassingFilterReads,y=meanCoverageP,)) 
  geom_point(aes(color="red", 
                 size=alignPercentR1>75)   
  ylim(0,70)   
  xlim(0,1500000000)  
  geom_hline(yintercept=30,
             color = "red", 
             linetype="dashed")

Error: unexpected symbol in: "ggplot(L2NEW,aes(x=PassingFilterReads,y=meanCoverageP,)) geom_point(aes(color="red", size=alignPercentR1>75)   ylim(0,70)   xlim(0,1500000000)  geom_hline(yintercept=30,color = "red", linetype

CodePudding user response：

It's helpful to provide an example of your data to help answer your question. Have a look here: How to make a great R reproducible example.

To add color, you can do the following:

library(tidyverse)

df <- 
  tibble(
    x = runif(100, 0, 100), 
    y = runif(100, 0, 100), 
    z = runif(100, 0, 100)
  )

ggplot(df)  
  aes(x = x, y = y, size = z, color = z)  
  geom_point()

To add your specific colors, the easiest way would be to add the colors into your data frame. This is because you have a continuous variable (size) to which you want to map a discrete aesthetic (color).

df <- 
  mutate(
    df, 
    clr = case_when(
      z > 75 ~ "red", 
      z > 25 ~ "blue", 
      TRUE ~ "green"
    )
  )

ggplot(df)  
  aes(x = x, y = y, size = z, color = clr)  
  geom_point()  
  scale_color_identity()

scale_color_identity will use the literal colors you've added to the clr column. If you want to define the palette in the plot code, use scale_color_manual and input your own vector of values.

CodePudding user response：

What about something like this:

library(dplyr)
L2NEW <- L2NEW %>% 
  mutate(group = case_when(
    alignPercentR1 > 75 ~ "High", 
    alignPercentR1 <= 75 & alignPercentR1 > 25 ~ "Middle", 
    alignPercentR1 <= 25 ~ "Low", 
    TRUE ~ NA_character_
  ), 
  group = factor(group, levels=c("Low", "Middle", "High")))

ggplot(L2NEW,aes(x=PassingFilterReads,y=meanCoverageP)) 
  geom_point(aes(size=alignPercentR1, colour=group))   
  scale_colour_manual(values=c("green", "blue", "red"))   
  ylim(0,60)   
  xlim(0,1500000000)  
  geom_hline(yintercept=30,
             color = "red", 
             linetype="dashed")