r - matching points on a tiled box plots to the proper category - Stack Overflow-软件玩家

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I want the code to make a plot where I color code exposure temperature points within boxes. But the code shown here maps the point colors to population, a different grouping factor. I can't get it to map to a different grouping factor and I am not 100% sure that the points are mapped to the correct box in the plot. I will paste the data beneath the code.

library(ggplot2)
library(dplyr)
library(ggnewscale)  # <-- Important for multiple color scales!

# Set the working directory (update if needed)
setwd("/")

# Load the dataset
df <- read.csv("2021experiment_qPCR_genes.csv")

# Define gene categories
gene_categories <- c(
  "CO1"   = "Mitochondrial",
  "RPS3"  = "Protein Synthesis",
  "RPS18" = "Protein Synthesis",
  "SDHBa" = "Metabolism",
  "SDHBb" = "Metabolism"
)

# Add new columns: GeneCategory, Population, ExposureTempC
df <- df %>%
  mutate(
    GeneCategory   = factor(gene_categories[Gene], 
                            levels = c("Mitochondrial", 
                                       "Protein Synthesis", 
                                       "Metabolism")),
    Population     = factor(Population, 
                            levels = c("Big Pine Creek", "Rock Creek")),  # Reversed order
    ExposureTempC  = factor(ExposureTempC, 
                            levels = c("20°C", "36°C"))  # Ensure Temperature is a factor
  )

# Define colors for temperature (36°C = red, 20°C = blue)
temp_colors <- c("20°C" = "blue", 
                 "36°C" = "red")

# Define colors for populations
population_colors <- c("Big Pine Creek" = "#9B1F38", 
                       "Rock Creek"     = "#1A2B80")

# -----------------------
# Create the plot (tiled)
# -----------------------
p <- ggplot(df, aes(x = Gene, y = BoxCoxCt)) +
  
  # 1) BOXES first: fill by GeneCategory, outline color by Population
  geom_boxplot(aes(fill = GeneCategory, color = Population),
               alpha = 0.5,
               outlier.shape = NA,  # removes outliers from boxplots
               size = 1,
               position = position_dodge(width = 0.75)) +
  
  # 2) Fill scale for GeneCategory
  scale_fill_manual(
    values = c("Mitochondrial"     = "#FFD700",
               "Protein Synthesis" = "#59D9C9",
               "Metabolism"        = "#B785D6"),
    name = "Gene Category"
  ) +
  
  # 3) First color scale: Population (box outlines)
  scale_color_manual(
    values = population_colors,
    name = "Population"
  ) +
  
  # 4) End that color scale; start a NEW one
  new_scale_color() +
  
  # 5) POINTS second: color by ExposureTempC
  geom_point(aes(color = ExposureTempC),
             size = 2, # smaller point size
             position = position_jitterdodge(
               jitter.width = 0.1, 
               dodge.width = 0.75
             )) +
  
  # 6) Second color scale: Temperature (points)
  scale_color_manual(
    values = temp_colors, 
    name = "Temperature"
  ) +
  
  # 7) Facet by RearingElev (stack CCR and OVS)
  facet_wrap(~ RearingElev, ncol = 1) +



  # 8) Theme adjustments
  theme_minimal() +
  theme(
    axis.text.x         = element_text(angle = 45, hjust = 1, size = 14),
    axis.text.y         = element_text(size = 14),
    axis.title.x        = element_text(size = 16),
    axis.title.y        = element_text(size = 16),
    strip.text.x        = element_text(size = 14),  # facet label size
    panel.grid          = element_blank(),          # remove grid lines
    panel.border        = element_blank(),          
    # Add BOTH top and bottom x-axis lines
    axis.line.x.bottom  = element_line(color = "black"),
    axis.line.x.top     = element_line(color = "black"),
    # Turn on y-axis line
    axis.line.y.left    = element_line(color = "black"),
    # Add y-axis ticks (and x ticks if desired)
    axis.ticks.y        = element_line(color = "black"),
    axis.ticks.x        = element_line(color = "black"),
    legend.position     = "right"
  ) +
  labs(
    x     = "Gene",
    y     = "Expression Value (Box-Cox)",
    title = "Gene Expression by Exposure Temperature and Population"
  ) +
  scale_x_discrete(position = "bottom")

# Save to PDF
pdf("gene_expression_plot_final_fixed.pdf", width = 8, height = 6)
print(p)
dev.off()

# Save to PNG
ggsave("gene_expression_plot_final_fixed.png", 
       plot   = p, 
       width  = 8, 
       height = 6, 
       units  = "in", 
       dpi    = 300)

# Show the plot
print(p)

Data:

structure(list(Population = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Big Pine Creek", 
"Rock Creek"), class = "factor"), RearingElev = c("CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)"), ExposureTempC = structure(c(2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("20°C", 
"36°C"), class = "factor"), Larva.ID = c("05B_3_CCR", "05B_3_CCR", 
"05B_3_CCR", "05B_3_CCR", "05B_3_CCR", "05C_2_OVS", "05C_2_OVS", 
"05C_2_OVS", "05C_2_OVS", "05C_2_OVS", "19B_2_CCR", "19B_2_CCR", 
"19B_2_CCR", "19B_2_CCR", "19B_2_CCR", "19B_2_OVS", "19B_2_OVS", 
"19B_2_OVS", "19B_2_OVS", "19B_2_OVS", "20A_4_OVS", "20A_4_OVS", 
"20A_4_OVS", "20A_4_OVS", "20A_4_OVS", "20B_2_CCR", "20B_2_CCR", 
"20B_2_CCR", "20B_2_CCR", "20B_2_CCR", "21B_3_OVS", "21B_3_OVS", 
"21B_3_OVS", "21B_3_OVS", "21B_3_OVS", "21C_1_CCR", "21C_1_CCR", 
"21C_1_CCR", "21C_1_CCR", "21C_1_CCR", "23A_1_OVS", "23A_1_OVS", 
"23A_1_OVS", "23A_1_OVS", "23A_1_OVS", "23A_4_CCR", "23A_4_CCR", 
"23A_4_CCR", "23A_4_CCR", "23A_4_CCR", "25C_2_CCR", "25C_2_CCR", 
"25C_2_CCR", "25C_2_CCR", "25C_2_CCR", "25C_2_OVS", "25C_2_OVS", 
"25C_2_OVS", "25C_2_OVS", "25C_2_OVS", "31A_2_CCR", "31A_2_CCR", 
"31A_2_CCR", "31A_2_CCR", "31A_2_CCR", "31A_4_OVS", "31A_4_OVS", 
"31A_4_OVS", "31A_4_OVS", "31A_4_OVS", "32B_3_OVS", "32B_3_OVS", 
"32B_3_OVS", "32B_3_OVS", "32B_3_OVS", "32C_1_CCR", "32C_1_CCR", 
"32C_1_CCR", "32C_1_CCR", "32C_1_CCR", "36D_4_CCR", "36D_4_CCR", 
"36D_4_CCR", "36D_4_CCR", "36D_4_CCR", "36D_4_OVS", "36D_4_OVS", 
"36D_4_OVS", "36D_4_OVS", "36D_4_OVS", "38B_1_OVS", "38B_1_OVS", 
"38B_1_OVS", "38B_1_OVS", "38B_1_OVS", "38B_3_CCR", "38B_3_CCR", 
"38B_3_CCR", "38B_3_CCR", "38B_3_CCR", "39A_1_OVS", "39A_1_OVS", 
"39A_1_OVS", "39A_1_OVS", "39A_1_OVS", "39A_4_CCR", "39A_4_CCR", 
"39A_4_CCR", "39A_4_CCR", "39A_4_CCR", "42B_2_OVS", "42B_2_OVS", 
"42B_2_OVS", "42B_2_OVS", "42B_2_OVS", "42B_4_CCR", "42B_4_CCR", 
"42B_4_CCR", "42B_4_CCR", "42B_4_CCR", "42C_1_CCR", "42C_1_CCR", 
"42C_1_CCR", "42C_1_CCR", "42C_1_CCR", "42C_1_OVS", "42C_1_OVS", 
"42C_1_OVS", "42C_1_OVS", "42C_1_OVS", "44A_2_CCR", "44A_2_CCR", 
"44A_2_CCR", "44A_2_CCR", "44A_2_CCR", "44A_4_OVS", "44A_4_OVS", 
"44A_4_OVS", "44A_4_OVS", "44A_4_OVS", "55B_1_CCR", "55B_1_CCR", 
"55B_1_CCR", "55B_1_CCR", "55B_1_CCR", "55C_1_OVS", "55C_1_OVS", 
"55C_1_OVS", "55C_1_OVS", "55C_1_OVS", "59A_1_CCR", "59A_1_CCR", 
"59A_1_CCR", "59A_1_CCR", "59A_1_CCR", "59A_3_OVS", "59A_3_OVS", 
"59A_3_OVS", "59A_3_OVS", "59A_3_OVS", "63B_2_CCR", "63B_2_CCR", 
"63B_2_CCR", "63B_2_CCR", "63B_2_CCR", "63B_2_OVS", "63B_2_OVS", 
"63B_2_OVS", "63B_2_OVS", "63B_2_OVS", "66A_4_CCR", "66A_4_CCR", 
"66A_4_CCR", "66A_4_CCR", "66A_4_CCR", "66B_2_OVS", "66B_2_OVS", 
"66B_2_OVS", "66B_2_OVS", "66B_2_OVS", "71C_2_OVS", "71C_2_OVS", 
"71C_2_OVS", "71C_2_OVS", "71C_2_OVS", "71C_4_CCR", "71C_4_CCR", 
"71C_4_CCR", "71C_4_CCR", "71C_4_CCR"), Gene = c("CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa"), BoxCoxCt = c(1153.785064, 
1153.3330972, 1157.8773038, 1160.7812295, 1159.3249702, 1152.8493979, 
1154.75196, 1158.6835238, 1163.3869751, 1159.5583676, 1158.0859612, 
1157.1054814, 1161.0814585, 1165.2628925, 1161.7629801, 1154.8156767, 
1154.1846296, 1159.0969046, 1162.5241738, 1158.3939237, 1156.8781143, 
1155.9550949, 1159.8049574, 1160.1069222, 1160.1499234, 1154.7576995, 
1154.3777093, 1158.7692338, 1155.8031171, 1158.0625595, 1157.6450891, 
1155.401337, 1158.656948, 1164.5433206, 1159.0369292, 1158.411655, 
1158.9713643, 1162.161972, 1165.2628925, 1163.1535991, 1152.1974566, 
1155.7117096, 1157.2384112, 1162.0448732, 1159.0986116, 1156.2027594, 
1152.0197466, 1158.4865631, 1161.5885228, 1159.3182609, 1158.9352635, 
1155.4319911, 1157.655569, 1163.1724474, 1158.903678, 1156.2767647, 
1154.7592593, 1158.497349, 1162.4112794, 1159.7530779, 1156.0211254, 
1155.1636002, 1158.9305397, 1159.8819075, 1159.5235572, 1157.6581236, 
1156.301795, 1159.2993927, 1163.3330524, 1160.3639047, 1152.1438019, 
1153.6118533, 1157.8648343, 1160.3079935, 1157.7549163, 1156.5418593, 
1154.5030424, 1159.6845041, 1159.4834108, 1160.7732796, 1156.1268851, 
1156.9471035, 1160.1082452, 1161.5752492, 1160.0179531, 1155.832561, 
1152.717972, 1158.923254, 1162.709987, 1158.1736444, 1156.8960868, 
1156.5195235, 1160.4082776, 1160.0356211, 1159.8817071, 1156.8808809, 
1156.6830702, 1160.4749978, 1161.9663674, 1160.9508598, 1160.6979716, 
1159.0821577, 1161.7138446, 1165.2628925, 1162.7049252, 1155.6792226, 
1154.5845231, 1158.2512588, 1163.4324569, 1159.5555489, 1155.1304113, 
1152.5885652, 1159.6718035, 1160.8696298, 1159.5094154, 1155.2197381, 
1155.13662, 1159.1715838, 1162.9341326, 1158.8529534, 1154.4527276, 
1155.8569068, 1160.3779861, 1165.2628925, 1162.3450309, 1157.9415546, 
1158.2822785, 1161.412776, 1161.734822, 1161.3289403, 1157.9835272, 
1155.1038908, 1159.1664836, 1165.2628925, 1162.0562191, 1156.4006477, 
1153.2992979, 1159.0969046, 1158.7499961, 1159.0751509, 1157.1356639, 
1155.0939147, 1161.0087539, 1162.1902394, 1159.7945789, 1154.8798219, 
1153.4340444, 1159.1868712, 1163.2046624, 1160.8414669, 1156.6351798, 
1155.6268737, 1157.843267, 1159.3384136, 1160.3927732, 1157.8533401, 
1156.907209, 1160.645019, 1163.3594653, 1161.6732296, 1155.8265797, 
1154.9015808, 1159.5084019, 1162.4742962, 1159.7715411, 1156.0299701, 
1154.9779641, 1159.0815017, 1163.0860174, 1159.0614443, 1156.2027594, 
1154.9635835, 1157.2740894, 1161.9420921, 1159.4754057, 1158.6100416, 
1155.5787524, 1159.5716703, 1164.3069188, 1160.0215643, 1158.9716479, 
1156.664008, 1159.4577399, 1164.3412959, 1159.0349658, 1158.0708384, 
1156.6818002, 1160.496847, 1164.3492107, 1160.6817049), GeneCategory = structure(c(CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L), levels = c("Mitochondrial", 
"Protein Synthesis", "Metabolism"), class = "factor")), class = "data.frame", row.names = c(NA, 
-190L))

library(ggplot2)
library(dplyr)
library(ggnewscale)  # <-- Important for multiple color scales!

# Set the working directory (update if needed)
setwd("/")

# Load the dataset
df <- read.csv("2021experiment_qPCR_genes.csv")

# Define gene categories
gene_categories <- c(
  "CO1"   = "Mitochondrial",
  "RPS3"  = "Protein Synthesis",
  "RPS18" = "Protein Synthesis",
  "SDHBa" = "Metabolism",
  "SDHBb" = "Metabolism"
)

# Add new columns: GeneCategory, Population, ExposureTempC
df <- df %>%
  mutate(
    GeneCategory   = factor(gene_categories[Gene], 
                            levels = c("Mitochondrial", 
                                       "Protein Synthesis", 
                                       "Metabolism")),
    Population     = factor(Population, 
                            levels = c("Big Pine Creek", "Rock Creek")),  # Reversed order
    ExposureTempC  = factor(ExposureTempC, 
                            levels = c("20°C", "36°C"))  # Ensure Temperature is a factor
  )

# Define colors for temperature (36°C = red, 20°C = blue)
temp_colors <- c("20°C" = "blue", 
                 "36°C" = "red")

# Define colors for populations
population_colors <- c("Big Pine Creek" = "#9B1F38", 
                       "Rock Creek"     = "#1A2B80")

# -----------------------
# Create the plot (tiled)
# -----------------------
p <- ggplot(df, aes(x = Gene, y = BoxCoxCt)) +
  
  # 1) BOXES first: fill by GeneCategory, outline color by Population
  geom_boxplot(aes(fill = GeneCategory, color = Population),
               alpha = 0.5,
               outlier.shape = NA,  # removes outliers from boxplots
               size = 1,
               position = position_dodge(width = 0.75)) +
  
  # 2) Fill scale for GeneCategory
  scale_fill_manual(
    values = c("Mitochondrial"     = "#FFD700",
               "Protein Synthesis" = "#59D9C9",
               "Metabolism"        = "#B785D6"),
    name = "Gene Category"
  ) +
  
  # 3) First color scale: Population (box outlines)
  scale_color_manual(
    values = population_colors,
    name = "Population"
  ) +
  
  # 4) End that color scale; start a NEW one
  new_scale_color() +
  
  # 5) POINTS second: color by ExposureTempC
  geom_point(aes(color = ExposureTempC),
             size = 2, # smaller point size
             position = position_jitterdodge(
               jitter.width = 0.1, 
               dodge.width = 0.75
             )) +
  
  # 6) Second color scale: Temperature (points)
  scale_color_manual(
    values = temp_colors, 
    name = "Temperature"
  ) +
  
  # 7) Facet by RearingElev (stack CCR and OVS)
  facet_wrap(~ RearingElev, ncol = 1) +



  # 8) Theme adjustments
  theme_minimal() +
  theme(
    axis.text.x         = element_text(angle = 45, hjust = 1, size = 14),
    axis.text.y         = element_text(size = 14),
    axis.title.x        = element_text(size = 16),
    axis.title.y        = element_text(size = 16),
    strip.text.x        = element_text(size = 14),  # facet label size
    panel.grid          = element_blank(),          # remove grid lines
    panel.border        = element_blank(),          
    # Add BOTH top and bottom x-axis lines
    axis.line.x.bottom  = element_line(color = "black"),
    axis.line.x.top     = element_line(color = "black"),
    # Turn on y-axis line
    axis.line.y.left    = element_line(color = "black"),
    # Add y-axis ticks (and x ticks if desired)
    axis.ticks.y        = element_line(color = "black"),
    axis.ticks.x        = element_line(color = "black"),
    legend.position     = "right"
  ) +
  labs(
    x     = "Gene",
    y     = "Expression Value (Box-Cox)",
    title = "Gene Expression by Exposure Temperature and Population"
  ) +
  scale_x_discrete(position = "bottom")

# Save to PDF
pdf("gene_expression_plot_final_fixed.pdf", width = 8, height = 6)
print(p)
dev.off()

# Save to PNG
ggsave("gene_expression_plot_final_fixed.png", 
       plot   = p, 
       width  = 8, 
       height = 6, 
       units  = "in", 
       dpi    = 300)

# Show the plot
print(p)

Data:

structure(list(Population = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Big Pine Creek", 
"Rock Creek"), class = "factor"), RearingElev = c("CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)", "CCR (3100 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", "OVS (1250 m)", 
"CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", "CCR (3100 m)", 
"CCR (3100 m)"), ExposureTempC = structure(c(2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("20°C", 
"36°C"), class = "factor"), Larva.ID = c("05B_3_CCR", "05B_3_CCR", 
"05B_3_CCR", "05B_3_CCR", "05B_3_CCR", "05C_2_OVS", "05C_2_OVS", 
"05C_2_OVS", "05C_2_OVS", "05C_2_OVS", "19B_2_CCR", "19B_2_CCR", 
"19B_2_CCR", "19B_2_CCR", "19B_2_CCR", "19B_2_OVS", "19B_2_OVS", 
"19B_2_OVS", "19B_2_OVS", "19B_2_OVS", "20A_4_OVS", "20A_4_OVS", 
"20A_4_OVS", "20A_4_OVS", "20A_4_OVS", "20B_2_CCR", "20B_2_CCR", 
"20B_2_CCR", "20B_2_CCR", "20B_2_CCR", "21B_3_OVS", "21B_3_OVS", 
"21B_3_OVS", "21B_3_OVS", "21B_3_OVS", "21C_1_CCR", "21C_1_CCR", 
"21C_1_CCR", "21C_1_CCR", "21C_1_CCR", "23A_1_OVS", "23A_1_OVS", 
"23A_1_OVS", "23A_1_OVS", "23A_1_OVS", "23A_4_CCR", "23A_4_CCR", 
"23A_4_CCR", "23A_4_CCR", "23A_4_CCR", "25C_2_CCR", "25C_2_CCR", 
"25C_2_CCR", "25C_2_CCR", "25C_2_CCR", "25C_2_OVS", "25C_2_OVS", 
"25C_2_OVS", "25C_2_OVS", "25C_2_OVS", "31A_2_CCR", "31A_2_CCR", 
"31A_2_CCR", "31A_2_CCR", "31A_2_CCR", "31A_4_OVS", "31A_4_OVS", 
"31A_4_OVS", "31A_4_OVS", "31A_4_OVS", "32B_3_OVS", "32B_3_OVS", 
"32B_3_OVS", "32B_3_OVS", "32B_3_OVS", "32C_1_CCR", "32C_1_CCR", 
"32C_1_CCR", "32C_1_CCR", "32C_1_CCR", "36D_4_CCR", "36D_4_CCR", 
"36D_4_CCR", "36D_4_CCR", "36D_4_CCR", "36D_4_OVS", "36D_4_OVS", 
"36D_4_OVS", "36D_4_OVS", "36D_4_OVS", "38B_1_OVS", "38B_1_OVS", 
"38B_1_OVS", "38B_1_OVS", "38B_1_OVS", "38B_3_CCR", "38B_3_CCR", 
"38B_3_CCR", "38B_3_CCR", "38B_3_CCR", "39A_1_OVS", "39A_1_OVS", 
"39A_1_OVS", "39A_1_OVS", "39A_1_OVS", "39A_4_CCR", "39A_4_CCR", 
"39A_4_CCR", "39A_4_CCR", "39A_4_CCR", "42B_2_OVS", "42B_2_OVS", 
"42B_2_OVS", "42B_2_OVS", "42B_2_OVS", "42B_4_CCR", "42B_4_CCR", 
"42B_4_CCR", "42B_4_CCR", "42B_4_CCR", "42C_1_CCR", "42C_1_CCR", 
"42C_1_CCR", "42C_1_CCR", "42C_1_CCR", "42C_1_OVS", "42C_1_OVS", 
"42C_1_OVS", "42C_1_OVS", "42C_1_OVS", "44A_2_CCR", "44A_2_CCR", 
"44A_2_CCR", "44A_2_CCR", "44A_2_CCR", "44A_4_OVS", "44A_4_OVS", 
"44A_4_OVS", "44A_4_OVS", "44A_4_OVS", "55B_1_CCR", "55B_1_CCR", 
"55B_1_CCR", "55B_1_CCR", "55B_1_CCR", "55C_1_OVS", "55C_1_OVS", 
"55C_1_OVS", "55C_1_OVS", "55C_1_OVS", "59A_1_CCR", "59A_1_CCR", 
"59A_1_CCR", "59A_1_CCR", "59A_1_CCR", "59A_3_OVS", "59A_3_OVS", 
"59A_3_OVS", "59A_3_OVS", "59A_3_OVS", "63B_2_CCR", "63B_2_CCR", 
"63B_2_CCR", "63B_2_CCR", "63B_2_CCR", "63B_2_OVS", "63B_2_OVS", 
"63B_2_OVS", "63B_2_OVS", "63B_2_OVS", "66A_4_CCR", "66A_4_CCR", 
"66A_4_CCR", "66A_4_CCR", "66A_4_CCR", "66B_2_OVS", "66B_2_OVS", 
"66B_2_OVS", "66B_2_OVS", "66B_2_OVS", "71C_2_OVS", "71C_2_OVS", 
"71C_2_OVS", "71C_2_OVS", "71C_2_OVS", "71C_4_CCR", "71C_4_CCR", 
"71C_4_CCR", "71C_4_CCR", "71C_4_CCR"), Gene = c("CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", 
"SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", 
"RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", 
"CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", 
"SDHBb", "SDHBa", "CO1", "RPS18", "RPS3", "SDHBb", "SDHBa", "CO1", 
"RPS18", "RPS3", "SDHBb", "SDHBa"), BoxCoxCt = c(1153.785064, 
1153.3330972, 1157.8773038, 1160.7812295, 1159.3249702, 1152.8493979, 
1154.75196, 1158.6835238, 1163.3869751, 1159.5583676, 1158.0859612, 
1157.1054814, 1161.0814585, 1165.2628925, 1161.7629801, 1154.8156767, 
1154.1846296, 1159.0969046, 1162.5241738, 1158.3939237, 1156.8781143, 
1155.9550949, 1159.8049574, 1160.1069222, 1160.1499234, 1154.7576995, 
1154.3777093, 1158.7692338, 1155.8031171, 1158.0625595, 1157.6450891, 
1155.401337, 1158.656948, 1164.5433206, 1159.0369292, 1158.411655, 
1158.9713643, 1162.161972, 1165.2628925, 1163.1535991, 1152.1974566, 
1155.7117096, 1157.2384112, 1162.0448732, 1159.0986116, 1156.2027594, 
1152.0197466, 1158.4865631, 1161.5885228, 1159.3182609, 1158.9352635, 
1155.4319911, 1157.655569, 1163.1724474, 1158.903678, 1156.2767647, 
1154.7592593, 1158.497349, 1162.4112794, 1159.7530779, 1156.0211254, 
1155.1636002, 1158.9305397, 1159.8819075, 1159.5235572, 1157.6581236, 
1156.301795, 1159.2993927, 1163.3330524, 1160.3639047, 1152.1438019, 
1153.6118533, 1157.8648343, 1160.3079935, 1157.7549163, 1156.5418593, 
1154.5030424, 1159.6845041, 1159.4834108, 1160.7732796, 1156.1268851, 
1156.9471035, 1160.1082452, 1161.5752492, 1160.0179531, 1155.832561, 
1152.717972, 1158.923254, 1162.709987, 1158.1736444, 1156.8960868, 
1156.5195235, 1160.4082776, 1160.0356211, 1159.8817071, 1156.8808809, 
1156.6830702, 1160.4749978, 1161.9663674, 1160.9508598, 1160.6979716, 
1159.0821577, 1161.7138446, 1165.2628925, 1162.7049252, 1155.6792226, 
1154.5845231, 1158.2512588, 1163.4324569, 1159.5555489, 1155.1304113, 
1152.5885652, 1159.6718035, 1160.8696298, 1159.5094154, 1155.2197381, 
1155.13662, 1159.1715838, 1162.9341326, 1158.8529534, 1154.4527276, 
1155.8569068, 1160.3779861, 1165.2628925, 1162.3450309, 1157.9415546, 
1158.2822785, 1161.412776, 1161.734822, 1161.3289403, 1157.9835272, 
1155.1038908, 1159.1664836, 1165.2628925, 1162.0562191, 1156.4006477, 
1153.2992979, 1159.0969046, 1158.7499961, 1159.0751509, 1157.1356639, 
1155.0939147, 1161.0087539, 1162.1902394, 1159.7945789, 1154.8798219, 
1153.4340444, 1159.1868712, 1163.2046624, 1160.8414669, 1156.6351798, 
1155.6268737, 1157.843267, 1159.3384136, 1160.3927732, 1157.8533401, 
1156.907209, 1160.645019, 1163.3594653, 1161.6732296, 1155.8265797, 
1154.9015808, 1159.5084019, 1162.4742962, 1159.7715411, 1156.0299701, 
1154.9779641, 1159.0815017, 1163.0860174, 1159.0614443, 1156.2027594, 
1154.9635835, 1157.2740894, 1161.9420921, 1159.4754057, 1158.6100416, 
1155.5787524, 1159.5716703, 1164.3069188, 1160.0215643, 1158.9716479, 
1156.664008, 1159.4577399, 1164.3412959, 1159.0349658, 1158.0708384, 
1156.6818002, 1160.496847, 1164.3492107, 1160.6817049), GeneCategory = structure(c(CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, 
SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, 
SDHBa = 3L, CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, 
CO1 = 1L, RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, 
RPS18 = 2L, RPS3 = 2L, SDHBb = 3L, SDHBa = 3L, CO1 = 1L, RPS18 = 2L, 
RPS3 = 2L, SDHBb = 3L, SDHBa = 3L), levels = c("Mitochondrial", 
"Protein Synthesis", "Metabolism"), class = "factor")), class = "data.frame", row.names = c(NA, 
-190L))

Share Improve this question edited Mar 6 at 13:32 stefan 127k6 gold badges38 silver badges76 bronze badges Recognized by R Language Collective asked Mar 6 at 5:58 n rank 311 silver badge1 bronze badge

2 Welcome to SO. Please replace your copy-and-paste of your csv file with the output of dput(df)) and remove all the code related to the construction of df: it’s simply not relevant. – Limey Commented Mar 6 at 6:05

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1 Answer 1

Sorted by: Reset to default 1

You are right. The points are assigned to the wrong boxes due to the different grouping, i.e. your box plots get dodged by Population whereas the points get dodged by ExposureTempC. To fix that you have to explicitly map Population on the group aes in geom_point.

As a check I added a geom_text layer.

library(ggplot2)
library(ggnewscale)

ggplot(df, aes(x = Gene, y = BoxCoxCt)) +
  geom_boxplot(aes(fill = GeneCategory, color = Population),
    alpha = 0.5,
    outlier.shape = NA, # removes outliers from boxplots
    size = 1,
    position = position_dodge(width = 0.75)
  ) +
  scale_fill_manual(
    values = c(
      "Mitochondrial" = "#FFD700",
      "Protein Synthesis" = "#59D9C9",
      "Metabolism" = "#B785D6"
    ),
    name = "Gene Category"
  ) +
  scale_color_manual(
    values = population_colors,
    name = "Population"
  ) +
  new_scale_color() +
  geom_point(
    aes(
      color = ExposureTempC,
      group = Population
    ),
    size = 2, # smaller point size
    position = position_jitterdodge(
      jitter.width = 0.1,
      dodge.width = 0.75,
    )
  ) +
  geom_text(
    aes(
      label = Population,
      group = Population
    ),
    size = 2, # smaller point size
    position = position_dodge(
      width = 0.75
    )
  ) +
  scale_color_manual(
    values = temp_colors,
    name = "Temperature"
  ) +
  facet_wrap(~RearingElev, ncol = 1) +
  theme_minimal() +
  theme(
    axis.text.x         = element_text(angle = 45, hjust = 1, size = 14),
    axis.text.y         = element_text(size = 14),
    axis.title.x        = element_text(size = 16),
    axis.title.y        = element_text(size = 16),
    strip.text.x        = element_text(size = 14), # facet label size
    panel.grid          = element_blank(), # remove grid lines
    panel.border        = element_blank(),
    axis.line.x.bottom  = element_line(color = "black"),
    axis.line.x.top     = element_line(color = "black"),
    axis.line.y.left    = element_line(color = "black"),
    axis.ticks.y        = element_line(color = "black"),
    axis.ticks.x        = element_line(color = "black"),
    legend.position     = "right"
  ) +
  labs(
    x     = "Gene",
    y     = "Expression Value (Box-Cox)",
    title = "Gene Expression by Exposure Temperature and Population"
  ) +
  scale_x_discrete(position = "bottom")

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