Color-coding data points in complex dotplot

[eimichae]

Hi there,
I produced a dot plot on 6 different treatments (trees under 6 different conditions; in column " Location.Treatment " in my raw data). For each of these “ Location.treatment” categories, I calculated a mean value and the SE for a specific compound (%CT).
I am able to produce a plot where all the 6 treatments (in column " Location.Treatment") are separated (see code and Fig in red&black) so that each of two "con" and "exp" treatments (in the column "treatment") are nested within one of the three locations (High, mid, low; in the column "Location") (see plot that the code produces). This is the plot structure I want.
Now I would like to assign colors to the raw data points ( the “point cloud” next to each mean +SE value). Each of these points stems from a different "Genotype" and I would like to color code the points with regard to the genotypes (e.g. all points from Genotype A should be green, all points from Genotype B should be red etc.) I would like to use my own specified colors in the code (not the standard palette).
I tried did the following (without success)

1. I added “aes(color=Genotype,….” into “geom_point(….)”
2. I added my specific colors to “scale_color_manual”
   scale_color_manual(labels=c("Control","Damaged"),values=c("red","black","#067c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3"......

However, if I do that my “nested” plot structure disappears (i.e. I cannot visually differentiate between “con” and “exp” treatments nested within mid /high/)

Basically, all I want is to produce a plot that looks like the one in the red&black Figure but where the individual data points are colored according to “Genotypes”
Below is my code, relevant figures and my raw data.
Help is very much appreciated!

# CODE
require(ggplot2)

#REMOVE START FOR ANALYSIS
dta<-subset(dta_complete,Time=="Stop")
dta

#Calculation of SE
data_summary <- function(x) {
  m <- mean(x)
  ymin <- m-sd(x)/sqrt(length(x))
  ymax <- m+sd(x)/sqrt(length(x))
  return(c(y=m,ymin=ymin,ymax=ymax))
}

pd1 = position_dodge(0.5)

plot_CT<- ggplot(dta, aes(x=Location, y=CT, colour=Treatment,shape=Treatment)) + 
  stat_summary(fun.data=data_summary, position=pd1, geom="errorbar", width=0.05) +
  stat_summary(fun.data=data_summary, position=pd1, geom="point", size=2) +
  geom_point(position=position_jitterdodge(dodge.width=0.8, jitter.height=0, jitter.width=0.2),
             alpha=0.7) +
  labs(title="", x="", y = "CT (% dw)")+
  scale_color_manual(labels=c("Control", "Damaged"),values=c("red","black"),guide = guide_legend(reverse = TRUE) )+
  scale_shape_manual(labels=c("Control", "Damaged"),name="Treatment",values = c(16,16),guide = guide_legend(reverse = TRUE) )+ 
  #Style of background
  theme_classic()+
  #Change title
  theme(plot.title = element_text(color="black", size=17, face="bold"))+
  #Font size axis
  theme(axis.text=element_text(size=12),
        axis.title=element_text(size=17))+
  scale_x_discrete("Location",labels = c("Low", "Mid", "High"),expand=c(0.1, 0.5))+
  coord_flip()

plot_CT
#CODE END

#RAW DATA

structure(list(Location = structure(c(2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), .Label = c("High", "Low", "Mid"
), class = "factor"), Treatment = structure(c(2L, 2L, 2L, 1L, 
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 
1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 
1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 
1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 
2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 
2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 
1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 
2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Con", "Exp"
), class = "factor"), Time = structure(c(2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Start", "Stop"
), class = "factor"), Genotype = structure(c(7L, 7L, 7L, 7L, 
7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 1L, 
1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 
4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 
6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 
7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 
1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 
7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 
1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 
8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("A", "B", 
"C", "D", "E", "F", "G", "H"), class = "factor"), Time.Location = structure(c(5L, 
6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 4L, 5L, 6L, 4L, 
5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 
6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 
4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 
5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 
6L, 4L, 5L, 6L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 
5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 
6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 
4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 
5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 
6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 
4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L), .Label = c("StartHigh", 
"StartLow", "StartMid", "StopHigh", "StopLow", "StopMid"), class = "factor"), 
    Location.Treatment = structure(c(4L, 6L, 2L, 3L, 5L, 1L, 
    4L, 6L, 2L, 3L, 5L, 1L, 4L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 
    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 
    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 
    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 
    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 
    5L, 1L, 4L, 6L, 2L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 
    2L, 3L, 5L, 1L), .Label = c("HighCon", "HighExp", "LowCon", 
    "LowExp", "MidCon", "MidExp"), class = "factor"), CT = c(4.61538, 
    3.96739, 7.34797, 3.58108, 2.89655, 2.7993, 10.56122, 10.68396, 
    15.57252, 6.79245, 9.23469, 9.18, 1.1087, 4.26136, 1.14504, 
    2.20238, 3.15789, 9.54082, 11.05263, 15.84783, 10.48986, 
    12.62195, 15.12931, 5.51471, 8.20313, 11.85811, 3.38115, 
    7.5, 9.69512, 8.64407, 11.30597, 14.42797, 8.8125, 11.82482, 
    11.53061, 6.97674, 9.62766, 10.88028, 5.50403, 9.73558, 8.56419, 
    11.84524, 16.34892, 18.15789, 10.58036, 14.80932, 12.06081, 
    12.96992, 9.86014, 12.45652, 6.625, 6.93396, 9.10714, 3.66142, 
    9.19811, 10.88346, 2.88851, 6.85096, 10.27778, 8.29787, 13.00885, 
    14.38017, 7.5, 11.77734, 13.84615, 2.22772, 5.28, 5.25641, 
    1.0514, 2.73256, 4.11111, 11.39098, 11.10236, 13.00781, 7.95259, 
    10.15748, 13.16327, 8.90625, 10.04587, 13.625, 6.27049, 9.27966, 
    10.94037, 5.80189, 7.76978, 7.34266, 3.80952, 3.75, 7.29545, 
    10.45872, 16.83206, 5.95238, 7.70833, 10.92391, 11.03659, 
    14.39338, 14.88281, 8.22917, 11.63603, 14.7561, 11.9469, 
    14.65649, 16.84615, 8.37209, 13.27982, 13.69128, 7.77778, 
    12.59124, 12.32955, 7.00472, 8.41121, 7.22222, 9.43878, 10.33613, 
    14.16667, 9.60526, 8.77232, 11.91589, 7.01786, 12.29592, 
    11.83673, 8.55634, 11.17347, 12.68836, 2.7551, 6, 7.21374, 
    2.52101, 4.03846, 4.80634, 5.49569, 4.78723, 6.02273, 3.04511, 
    3.59244, 2.48239, 1.54412, 5.74219, 7.68595, 1.33065, 2.625, 
    4.42164, 9.66942, 11.875, 17.91667, 10.81731, 13.05288, 16.23853, 
    11.93662, 14.31818, 14.09396, 7.82374, 15.5042, 10.86207, 
    6.87023, 11.69492, 12.65957, 3.48684, 5.29018, 7.89474, 10.53309, 
    17.05479, 16.63866, 7.43119, 12.06522, 12.05607, 6.14865, 
    10.44, 14.69512, 9.24757, 9.04018, 12.38255, 2.22222, 3.90756, 
    5.85616, 2.23958, 3.8125, 3.01056, 11.60256, 12.22222, 11.8007, 
    7.76316, 10.08197, 12.78777, 9.20455, 12.1875, 16.59449, 
    6.82331, 10.91518, 11.5748)), row.names = 192:381, class = "data.frame")

[mara]

You're close, there are just a few changes you need to make:

Note that I removed colour = Treatment in the top ggplot() call because you don't want to colour by Treatment, you want to colour by Genotype. The aes() for geom_point() is where I've added colour = Genotype, since you want just the points coloured.

The other change was that I removed labels = c("...") from your scale_colour_manual(). If you are going to specify labels, you should specify them for all of the values you're using.

Note also that the scale_shape_manual() call specifies the same shape for both groups. I'm not sure if this is intentional or not, so I didn't touch it.

# CODE
library(tidyverse)

# REMOVE START FOR ANALYSIS
dta <- structure(list(
  Location = structure(c(
    2L, 3L, 1L, 2L, 3L, 1L,
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
    1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
    3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
    1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
    3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
    1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
    3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
    1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
    2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
    3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L
  ), .Label = c("High", "Low", "Mid"), class = "factor"), Treatment = structure(c(
    2L, 2L, 2L, 1L,
    1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
    1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
    2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L,
    1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L,
    1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
    2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
    2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
    1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
    2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
    2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L,
    1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L,
    2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L
  ), .Label = c("Con", "Exp"), class = "factor"), Time = structure(c(
    2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
  ), .Label = c("Start", "Stop"), class = "factor"), Genotype = structure(c(
    7L, 7L, 7L, 7L,
    7L, 7L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 2L, 2L, 2L,
    2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 1L,
    1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L,
    4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L,
    6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 5L, 5L, 5L, 5L, 7L,
    7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L,
    1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
    4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L,
    7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L,
    2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L,
    1L, 1L, 5L, 5L, 5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L,
    8L, 8L, 8L, 8L, 4L, 4L, 4L, 4L, 4L, 4L
  ), .Label = c(
    "A", "B",
    "C", "D", "E", "F", "G", "H"
  ), class = "factor"), Time.Location = structure(c(
    5L,
    6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 4L, 5L, 6L, 4L,
    5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
    6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
    4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
    5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
    6L, 4L, 5L, 6L, 4L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
    5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
    6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
    4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L,
    5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L,
    6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L,
    4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L, 5L, 6L, 4L
  ), .Label = c(
    "StartHigh",
    "StartLow", "StartMid", "StopHigh", "StopLow", "StopMid"
  ), class = "factor"),
  Location.Treatment = structure(c(
    4L, 6L, 2L, 3L, 5L, 1L,
    4L, 6L, 2L, 3L, 5L, 1L, 4L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
    5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L,
    6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L,
    5L, 1L, 4L, 6L, 2L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
    2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L,
    1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L, 2L, 3L, 5L, 1L, 4L, 6L,
    2L, 3L, 5L, 1L
  ), .Label = c(
    "HighCon", "HighExp", "LowCon",
    "LowExp", "MidCon", "MidExp"
  ), class = "factor"), CT = c(
    4.61538,
    3.96739, 7.34797, 3.58108, 2.89655, 2.7993, 10.56122, 10.68396,
    15.57252, 6.79245, 9.23469, 9.18, 1.1087, 4.26136, 1.14504,
    2.20238, 3.15789, 9.54082, 11.05263, 15.84783, 10.48986,
    12.62195, 15.12931, 5.51471, 8.20313, 11.85811, 3.38115,
    7.5, 9.69512, 8.64407, 11.30597, 14.42797, 8.8125, 11.82482,
    11.53061, 6.97674, 9.62766, 10.88028, 5.50403, 9.73558, 8.56419,
    11.84524, 16.34892, 18.15789, 10.58036, 14.80932, 12.06081,
    12.96992, 9.86014, 12.45652, 6.625, 6.93396, 9.10714, 3.66142,
    9.19811, 10.88346, 2.88851, 6.85096, 10.27778, 8.29787, 13.00885,
    14.38017, 7.5, 11.77734, 13.84615, 2.22772, 5.28, 5.25641,
    1.0514, 2.73256, 4.11111, 11.39098, 11.10236, 13.00781, 7.95259,
    10.15748, 13.16327, 8.90625, 10.04587, 13.625, 6.27049, 9.27966,
    10.94037, 5.80189, 7.76978, 7.34266, 3.80952, 3.75, 7.29545,
    10.45872, 16.83206, 5.95238, 7.70833, 10.92391, 11.03659,
    14.39338, 14.88281, 8.22917, 11.63603, 14.7561, 11.9469,
    14.65649, 16.84615, 8.37209, 13.27982, 13.69128, 7.77778,
    12.59124, 12.32955, 7.00472, 8.41121, 7.22222, 9.43878, 10.33613,
    14.16667, 9.60526, 8.77232, 11.91589, 7.01786, 12.29592,
    11.83673, 8.55634, 11.17347, 12.68836, 2.7551, 6, 7.21374,
    2.52101, 4.03846, 4.80634, 5.49569, 4.78723, 6.02273, 3.04511,
    3.59244, 2.48239, 1.54412, 5.74219, 7.68595, 1.33065, 2.625,
    4.42164, 9.66942, 11.875, 17.91667, 10.81731, 13.05288, 16.23853,
    11.93662, 14.31818, 14.09396, 7.82374, 15.5042, 10.86207,
    6.87023, 11.69492, 12.65957, 3.48684, 5.29018, 7.89474, 10.53309,
    17.05479, 16.63866, 7.43119, 12.06522, 12.05607, 6.14865,
    10.44, 14.69512, 9.24757, 9.04018, 12.38255, 2.22222, 3.90756,
    5.85616, 2.23958, 3.8125, 3.01056, 11.60256, 12.22222, 11.8007,
    7.76316, 10.08197, 12.78777, 9.20455, 12.1875, 16.59449,
    6.82331, 10.91518, 11.5748
  )
), row.names = 192:381, class = "data.frame")

# Calculation of SE
data_summary <- function(x) {
  m <- mean(x)
  ymin <- m - sd(x) / sqrt(length(x))
  ymax <- m + sd(x) / sqrt(length(x))
  return(c(y = m, ymin = ymin, ymax = ymax))
}

pd1 <- position_dodge(0.5)

plot_CT <- ggplot(dta, aes(x = Location, y = CT, group = Treatment, shape = Treatment)) +
  stat_summary(fun.data = data_summary, position = pd1, geom = "errorbar", width = 0.05) +
  stat_summary(fun.data = data_summary, position = pd1, geom = "point", size = 2) +
  geom_point(aes(colour = Genotype),
    position = position_jitterdodge(dodge.width = 0.8, jitter.height = 0, jitter.width = 0.2),
    alpha = 0.7
  ) +
  labs(title = "", x = "", y = "CT (% dw)") +
  # scale_color_manual(labels=c("Control", "Damaged"),values=c("red","black"),guide = guide_legend(reverse = TRUE) )+
  scale_color_manual(values=c("red","black","#067c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3")) +
  scale_shape_manual(labels = c("Control", "Damaged"), name = "Treatment", values = c(16, 16), guide = guide_legend(reverse = TRUE)) +
  # Style of background
  theme_classic() +
  # Change title
  theme(plot.title = element_text(color = "black", size = 17, face = "bold")) +
  # Font size axis
  theme(
    axis.text = element_text(size = 12),
    axis.title = element_text(size = 17)
  ) +
  scale_x_discrete("Location", labels = c("Low", "Mid", "High"), expand = c(0.1, 0.5)) +
  coord_flip()

plot_CT

^{Created on 2019-04-08 by the reprex package (v0.2.1)}

[eimichae]

Hi Mara
Thank you very much for this swift response and your solution!
I have two more questions:
1:
Is it possible to change the shapes of the mean values of the two groups but not for the associated data points of the "point cloud"? I.e the black "control" symbols should be round and the black "damaged" symbols should be squares but all colored data points should remain round?
if I cange the values in "scale_shape...." (see below) it affects both the black mean symbols as well as the coloured data points

#CODE
scale_shape_manual(labels = c("Control", "Damaged"), name = "Treatment", values = c(16, 15), guide = guide_legend(reverse = TRUE)) +
#CODE END

2:
Is it possible to make the legend for "Genotype" disappear but to keept the "Treatment" legend?

Thanks a lot

[mara]

@eimichae

Is it possible to change the shapes of the mean values of the two groups but not for the associated data points of the "point cloud"? I.e the black "control" symbols should be round and the black "damaged" symbols should be squares but all colored data points should remain round?

I believe so. However, you'll have to specify the shape outside of the first ggplot() call, I believe.

@eimichae

Is it possible to make the legend for "Genotype" disappear but to keept the "Treatment" legend?

Yes, you do this by adding show.legend = FALSE to the geom for which you don't want a legend

That would look like:

plot_CT <- ggplot(dta, aes(x = Location, y = CT, group = Treatment, shape = Treatment)) +
  stat_summary(fun.data = data_summary, position = pd1, geom = "errorbar", width = 0.05) +
  stat_summary(fun.data = data_summary, position = pd1, geom = "point", size = 2) +
  geom_point(aes(colour = Genotype),
             position = position_jitterdodge(dodge.width = 0.8, jitter.height = 0, jitter.width = 0.2),
             alpha = 0.7, show.legend = FALSE
  ) +
  labs(title = "", x = "", y = "CT (% dw)") +
  # scale_color_manual(labels=c("Control", "Damaged"),values=c("red","black"),guide = guide_legend(reverse = TRUE) )+
  scale_color_manual(values=c("red","black","#067c43","#89b651","#dc5b09","#e4a710","#92c5de","grey","#1d71b4","#7873a3")) +
  scale_shape_manual(labels = c("Control", "Damaged"), name = "Treatment", values = c(16, 16), guide = guide_legend(reverse = TRUE)) +
  # Style of background
  theme_classic() +
  # Change title
  theme(plot.title = element_text(color = "black", size = 17, face = "bold")) +
  # Font size axis
  theme(
    axis.text = element_text(size = 12),
    axis.title = element_text(size = 17)
  ) +
  scale_x_discrete("Location", labels = c("Low", "Mid", "High"), expand = c(0.1, 0.5)) +
  coord_flip()

plot_CT

[eimichae]

Hi Mara,
I updated the code now. I had to add aes(shape = Treatment) to one of the stat_summary functions. This did the trick.

# Code
  stat_summary(fun.data = data_summary, position = position_dodge(0.5), geom = "point",aes(shape = Treatment), size = 2,color="black") +

Thank you very much for your help.

[andresrcs]

If your question's been answered (even by you!), would you mind choosing a solution? It helps other people see which questions still need help, or find solutions if they have similar problems. Here’s how to do it:

FAQ: How do I mark a solution?

If your question has been answered, don't forget to mark the solution! How do I mark a solution? Find the reply you want to mark as the solution and look for the row of small gray icons at the bottom of that reply. Click the one that looks like a box with a checkmark in it: [image] Hovering over the mark solution button shows the label, "Select if this reply solves the problem". If you don't see the mark solution button, try clicking the three dots button ( ••• ) to expand the full set of options. When a solution is chosen, the icon turns green and the hover label changes to: "Unselect if this reply no longer solves the problem". Success! [solution_reply_author] …