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I'm plotting scRNA data using Violin Plots. I need to re-order the plots and add median dots. My code is:

Vln_plot <- VlnPlot(object, 
                    features = c("Mcidas"), 
                    cols = c("coral1", "cadetblue", "cadetblue2"), 
                    split.by = "genotype",
                    assay = "RNA",
                    pt.size = 0,
                    log = TRUE) + 
  stat_summary(fun.y = median.stat, geom='point', size = 10, colour = "blue",
               position = position_dodge(0.9)) 
  

Vln_plot$data$split<- factor(x = Vln_plot$data$split,
                                 levels = c("WT", "F7KO", "F8HET"))

Vln_plot

median.stat <- function(x){
  out <- quantile(x, probs = c(0.5))
  names(out) <- c("ymed")
  return(out) 
}

and my output looks like: enter image description here

Is there any way to fix the legend so those dots aren't in each box? I also need to figure out how to get rid of that x-axis tic mark and change the x axis label from Identity to something else. Can anyone point me in the right direction on how to accomplish this?

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  • $\begingroup$ Is there any way to give us an example with some sort of toy dataset we can use for testing? Various R libraries include example data, any chance you could provide such an example? $\endgroup$
    – terdon ♦
    Feb 3 at 12:22

2 Answers 2

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Your command looks like it creates a ggplot2 object, so it should be possible to remove the symbol via guides, setting the associated aesthetic to "none":

Vln_plot <- VlnPlot(object, 
                    features = c("Mcidas"), 
                    cols = c("coral1", "cadetblue", "cadetblue2"), 
                    split.by = "genotype",
                    assay = "RNA",
                    pt.size = 0,
                    log = TRUE) + 
  stat_summary(fun.y = median.stat, geom='point', size = 10, colour = "blue",
               position = position_dodge(0.9)) +
  guides(color = "none")

If that doesn't work, try telling the stat_summary command to disable the legend via show.legend = FALSE:

Vln_plot <- VlnPlot(object, 
                    features = c("Mcidas"), 
                    cols = c("coral1", "cadetblue", "cadetblue2"), 
                    split.by = "genotype",
                    assay = "RNA",
                    pt.size = 0,
                    log = TRUE) + 
  stat_summary(fun.y = median.stat, geom='point', size = 10, colour = "blue",
               position = position_dodge(0.9), show.legend = FALSE)
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If you can provide a minimal reproducible example with a 'cut-down' version of your data it would be a lot easier to answer your question. I have an example from a similar question on stackoverflow (https://stackoverflow.com/a/73696447/12957340) that illustrates one approach to your problem:

# Load libraries
library(tidyverse)

# Load example data
raw_data <- structure(list(Type = c("EY", "EY", "EY", "EY", "EY", "EY", "EY", 
                                    "EY", "EY", "EY", "EY", "EY", "EO", "EO", "EO", "EO", "EO", "EO", 
                                    "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EY", "EY", 
                                    "EY", "EY", "EY", "EY", "EY", "EY", "EY", "EY", "EY", "EY", "EO", 
                                    "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", "EO", 
                                    "EO", "EO", "EO", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", 
                                    "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", 
                                    "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", 
                                    "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe", "Fe"), 
                           Maturity = 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, 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, 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), .Label = c("Before", 
                                                                                                      "After"), class = "factor"), Mn = c(49.65414679, 30.42267647, 
                                                                                                                                          53.57468125, 58.38531743, 11.07088615, 45.10644112, 41.33779076, 
                                                                                                                                          18.77426257, 60.36149117, 67.0260032, 38.13116392, 69.58713059, 
                                                                                                                                          66.80825471, 30.34496525, 56.90875291, 72.37427455, 22.06855022, 
                                                                                                                                          39.26030375, 35.31067394, 24.95698024, 24.88586385, 34.65821779, 
                                                                                                                                          56.2750941, 19.56655377, 45.04117517, 44.04604616, 30.4130276, 
                                                                                                                                          15.76824315, 21.50636001, 27.25777212, 17.08214603, 14.17493713, 
                                                                                                                                          34.24593956, 12.39548126, 23.59787998, 38.42021152, 32.54843776, 
                                                                                                                                          18.47119505, 26.05687922, 32.97977895, 16.91703485, 30.0626039, 
                                                                                                                                          26.72724955, 17.69433512, 22.34314521, 16.73815161, 13.08749188, 
                                                                                                                                          19.60771131, 24.08865106, 34.57472809, 14.94650052, 32.60745327, 
                                                                                                                                          29.86439635, 20.71564742, 22.32568148, 18.37220522, 24.22830773, 
                                                                                                                                          20.91660251, 20.96486868, 34.25266591, 35.57200211, 14.5736099, 
                                                                                                                                          25.67187037, 27.7352539, 42.919751, 27.1949762, 18.94238981, 
                                                                                                                                          25.25867502, 31.66215867, 18.1734287, 24.41910112, 12.07438938, 
                                                                                                                                          12.85034127, 19.75012923, 35.96030792, 30.07986478, 38.91460672, 
                                                                                                                                          41.18492241, 41.68085289, 60.93940724, 49.77930187, 17.56806894, 
                                                                                                                                          37.13306953, 47.06926881, 85.62093648, 24.31500546, 22.049633, 
                                                                                                                                          40.42923285, 87.53339143, 37.08699364, 38.29525586, 28.00272281, 
                                                                                                                                          15.58855204, 37.14164977)), row.names = c(NA, -94L), class = c("tbl_df", 
                                                                                                                                                                                                         "tbl", "data.frame"))

Functions:

summary_df <- raw_data %>%
  mutate(Maturity = ifelse(Maturity == "Before", "a", "x")) %>%
  group_by(Type, Maturity) %>%
  summarise(max_val = max(density(Mn)[[1]]) + 4) %>%
  ungroup()

median.stat <- function(x){
  out <- quantile(x, probs = c(0.5))
  names(out) <- c("ymed")
  return(out) 
}

Similar 'problematic' violin plot:

ggplot(raw_data, aes(x = Type, y = Mn, fill = Maturity)) +
  geom_violin(trim = FALSE, position="dodge") + 
  geom_boxplot(width=.1, outlier.shape=NA, position=position_dodge(.9)) +  
  scale_y_continuous(breaks = seq(0, 100, 25)) +
  theme_classic() + 
  theme(axis.title.x = element_blank(),
        axis.ticks.x = element_blank()) + 
  labs(y="Percent Maturity", x= "") +
  geom_text(data = summary_df,
            aes(label = Maturity,
                y = max_val,
                x = Type,
                group = Maturity),
            position = position_dodge(width = 0.9),
            check_overlap = TRUE,
            show.legend = FALSE,
            inherit.aes = FALSE) +
  stat_summary(fun.y = median.stat, geom='point', size = 10, colour = "blue",
               position = position_dodge(0.9))
#> Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
#> ℹ Please use the `fun` argument instead.

Remove dots:

ggplot(raw_data, aes(x = Type, y = Mn, fill = Maturity)) +
  geom_violin(trim = FALSE, position="dodge") + 
  geom_boxplot(width=.1, outlier.shape=NA, position=position_dodge(.9)) +  
  scale_y_continuous(breaks = seq(0, 100, 25)) +
  theme_classic() + 
  theme(axis.title.x = element_blank(),
        axis.ticks.x = element_blank()) + 
  labs(y="Percent Maturity", x= "") +
  geom_text(data = summary_df,
            aes(label = Maturity,
                y = max_val,
                x = Type,
                group = Maturity),
            position = position_dodge(width = 0.9),
            check_overlap = TRUE,
            show.legend = FALSE,
            inherit.aes = FALSE) +
  stat_summary(fun.y = median.stat, geom='point', size = 10, colour = "blue",
               position = position_dodge(0.9), key_glyph = "blank")

Remove dots, but keep 'colour' legend to specify what the dots represent:

ggplot(raw_data, aes(x = Type, y = Mn, fill = Maturity)) +
  geom_violin(trim = FALSE, position="dodge") + 
  geom_boxplot(width=.1, outlier.shape=NA,  position=position_dodge(.9), key_glyph = "boxplot") +  
  scale_y_continuous(breaks = seq(0, 100, 25)) +
  theme_classic() + 
  theme(axis.title.x = element_blank(),
        axis.ticks.x = element_blank()) + 
  labs(y="Percent Maturity", x= "") +
  geom_text(data = summary_df,
            aes(label = Maturity,
                y = max_val,
                x = Type,
                group = Maturity),
            position = position_dodge(width = 0.9),
            check_overlap = TRUE,
            show.legend = FALSE,
            inherit.aes = FALSE) +
  stat_summary(aes(colour = "Median"), fun.y = median.stat, 
               geom='point', size = 10,
               position = position_dodge(0.9)) +
  scale_color_manual(values = "blue", name = "Statistics") +
  guides(fill = guide_legend(override.aes = list(shape = NA)))

Created on 2023-02-08 with reprex v2.0.2

Hopefully this approach can be adapted to your use-case.

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