gg_manhattan()

The function gg_Manhattan() creates manhattan plots from GAPIT GWAS results.

Specifying a folder and trait is all that is needed to create manhattan plots.

# Plot
mp <- gg_Manhattan(
  # Specify a folder with GWAS results
  folder = "GWAS_Results/", 
  # Select a trait to plot
  trait = "DTF_Nepal_2017" )
# Save
ggsave("figures/gg_Manhattan_01_DTF_Nepal_2017.png", 
       mp, width = 12, height = 3.5, bg = "white")

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Plot all traits with a loop

A simple loop can be used to plot GWAS results for each trait within the specified folder.

# Create for loop
for(i in list_Traits(folder = "GWAS_Results/")) {
  # Plot
  mp <- gg_Manhattan(
    # Specify a folder with GWAS results
    folder = "GWAS_Results/", 
    # Select a trait to plot
    trait = i )
  # Save
  ggsave(paste0("figures/gg_Manhattan_01_", i, ".png"), 
         mp, width = 12, height = 3.5, bg = "white")
}

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Facetting

The default setting for gg_Manhattan() is to set facet = F which will plot all models together. By changing facet = T we can separate each GWAS model. When setting facet = T, points are now colored by chromosome, which can be changed with chr.colors. Significant associations can also be highlighted by setting highlight.sig and sig.color.

# Plot
mp <- gg_Manhattan(
  # Specify a folder with GWAS results
  folder = "GWAS_Results/",
  # Select a trait to plot
  trait = "Cotyledon_RedvsYellow", 
  # Facet out the different GWAS models
  facet = T,
  # Set chromosome colors
  chr.colors = rep(c("darkgreen", "darkgoldenrod3"), 4),
  # Highlight significant associations
  highlight.sig = T,
  # Choose the highlight color
  sig.color = "darkred" )
# Save
ggsave("figures/gg_Manhattan_02_Cotyledon_RedvsYellow.png", 
       mp, width = 12, height = 8, bg = "white")

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Single Chromosome

A single chromosome can be plotted by setting chr. The x-axis can also be adjusted by setting chr.unit.

# Plot
mp <- gg_Manhattan(
  # Specify a folder with GWAS results
  folder = "GWAS_Results/", 
  # Select a trait to plot
  trait = "DTF_Nepal_2017",
  # Select a chromosome to plot
  chr = 2,
  # Change chromosome units
  chr.unit = "50 Mbp" )
# Save
ggsave("figures/gg_Manhattan_03_DTF_Nepal_2017.png", 
       mp, width = 7, height = 3.5, bg = "white")

---

Customized Plot

The default for gg_Manhattan() is to set the plot title = trait, but this can be changed. You can also adjust the threshold and add asug.threshold. If specified, markers can be highlighted and have their labels customized. Adding vlines can be used to aid in comparisons with other manhattan plots or accross GWAS models. vlines can be customized with vline.colors and vline.types. You can Select which GWAS models to plot and set the colors of each with model.colors. Significant associations can also be highlighted by setting highlight.sig and sig.color. The QQ plot can also be removed by setting addQQ = F.

# Plot
mp <- gg_Manhattan(
  # Specify a folder with GWAS results
  folder = "GWAS_Results/",
  # Select a trait to plot
  trait = "DTF_Nepal_2017",
  # Create a title for the plot
  title = "DTF Sask 2017",
  # Set horizontal thresholds bars
  threshold = 6.7,
  sug.threshold = 5,
  # Highlight specific markers
  markers = c("Lcu.1GRN.Chr2p44545877",
             "Lcu.1GRN.Chr5p1658484"),
  labels = c("p44545877",
             "p1658484"),
  # Add vertical lines
  vlines = c("Lcu.1GRN.Chr2p44545877",
             "Lcu.1GRN.Chr5p1658484",
             "Lcu.1GRN.Chr6p3269280"),
  vline.colors = c("red","red","blue"),
  vline.types = c(1,1,2),
  # Change the legend alignment
  legend.box="vertical",
  # Select GWAS models
  models = c("MLM", "MLMM", "FarmCPU", "BLINK"),
  # Set colors for each GWAS model
  model.colors = c("darkgreen", "darkred", "darkorange3", "steelblue"),
  # Highlight significant associations
  highlight.sig = T,
  # Highlight color
  sig.color = "black",
  # Remove the QQ plot
  addQQ = F)
# Save
ggsave("figures/gg_Manhattan_04_DTF_Nepal_2017.png", 
       mp, width = 8, height = 3.5, bg = "white")

---

# Plot
mp <- gg_Manhattan(
  # Specify a folder with GWAS results
  folder = "GWAS_Results/",
  # Select a trait to plot
  trait = "DTF_Sask_2017_b",
  # Create a title for the plot
  title = "DTF Sask 2017 | Covariate = b",
  # Set horizontal thresholds bars
  threshold = 6.7,
  sug.threshold = 5,
  # Highlight specific markers
  markers = "Lcu.1GRN.Chr6p3269280",
  labels = "p3269280",
  # Add vertical lines
  vlines = c("Lcu.1GRN.Chr2p44545877",
             "Lcu.1GRN.Chr5p1658484",
             "Lcu.1GRN.Chr6p3269280"),
  vline.colors = c("red","red","blue"),
  vline.types = c(2,2,1),
  # Change the legend alignment
  legend.box="vertical",
  # Select GWAS models
  models = c("MLM", "MLMM", "FarmCPU", "BLINK"),
  # Set colors for each GWAS model
  model.colors = c("darkgreen", "darkred", "darkorange3", "steelblue"),
  # Highlight significant associations
  highlight.sig = T,
  # Highlight color
  sig.color = "black",
  # Remove the QQ plot
  addQQ = F)
# Save
ggsave("figures/gg_Manhattan_04_DTF_Sask_2017_b.png", 
       mp, width = 8, height = 3.5, bg = "white")

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