Plots of % mitochondrial reads and cardiolipin

This article generates plots of % mitochondrial reads and cardiolipin (Fig. 5C).

library(MotrpacRatTraining6moWATData)
library(MotrpacRatTraining6moData) # TRNSCRPT_META
library(dplyr)
library(ggplot2)
library(Biobase)
library(ggbeeswarm)

save_plots <- dir.exists(paths = file.path("..", "..", "plots"))

# Reformat data for plotting
mito <- TRNSCRPT_META %>%
  filter(grepl("white adipose", Tissue, ignore.case = TRUE)) %>%
  dplyr::rename(bid = BID) %>%
  inner_join(pData(TRNSCRPT_EXP), by = "bid") %>%
  mutate(prop_mt = pct_chrM / 100)

# Plot % mitochondrial reads
mito_reads <- ggplot(mito, aes(x = timepoint, y = pct_chrM)) +
  stat_summary(fun.data = "mean_sdl",
               fun.args = list(mult = 1),
               mapping = aes(color = sex),
               show.legend = FALSE,
               geom = "crossbar", width = 0.8,
               na.rm = TRUE, fatten = 1, size = 0.3) +
  ggbeeswarm::geom_beeswarm(size = 0.5, cex = 3, groupOnX = TRUE) +
  scale_color_manual(values = c("#ff6eff", "#3366ff"),
                     breaks = c("Female", "Male")) +
  guides(color = guide_none()) +
  facet_wrap(~ sex, nrow = 1) +
  scale_y_continuous(limits = c(3.4, 6)) +
  coord_cartesian(ylim = c(3.5, NA)) +
  labs(x = NULL,
       y = "% Mitochondrial Reads",
       title = "Mitochondrial Reads in RNA-Seq") +
  theme_minimal(base_size = 6) +
  theme(axis.text.x = element_text(color = "black",
                                   size = 5, angle = 90,
                                   vjust = 0.5, hjust = 1),
        axis.text.y = element_text(color = "black", size = 5),
        axis.title.y = element_text(color = "black", size = 6.5),
        plot.title = element_text(color = "black",size = 6.5),
        panel.grid = element_blank(),
        axis.ticks.y = element_line(color = "black", size = 0.3),
        axis.line = element_line(color = "black", size = 0.3),
        plot.background = element_rect(fill = "white",
                                       color = NA),
        legend.text = element_text(color = "black", size = 5),
        legend.title = element_text(color = "black", size = 5),
        strip.text = element_text(color = "black", size = 6.5))

mito_reads

ggsave(file.path("..", "..", "plots", "pct_mito_reads.pdf"), mito_reads,
       height = 1.4, width = 1.5, family = "ArialMT")

## Testing
# Males
kruskal.test(prop_mt ~ timepoint, data = filter(mito, sex == "Male"))
#> 
#>  Kruskal-Wallis rank sum test
#> 
#> data:  prop_mt by timepoint
#> Kruskal-Wallis chi-squared = 0.433, df = 4, p-value = 0.9797
# Kruskal-Wallis chi-squared = 0.433, df = 4, p-value = 0.9797

# Females
kruskal.test(prop_mt ~ timepoint, data = filter(mito, sex == "Female"))
#> 
#>  Kruskal-Wallis rank sum test
#> 
#> data:  prop_mt by timepoint
#> Kruskal-Wallis chi-squared = 5.417, df = 4, p-value = 0.2471
# Kruskal-Wallis chi-squared = 5.417, df = 4, p-value = 0.2471

# Plot cardiolipin
METAB_EXP$cardiolipin <- exprs(METAB_EXP)["CL(72:8)_feature1", ]

cl <- ggplot(pData(METAB_EXP),
             aes(x = timepoint, y = cardiolipin)) +
  stat_summary(fun.data = "mean_sdl",
               fun.args = list(mult = 1),
               mapping = aes(color = sex),
               show.legend = FALSE,
               geom = "crossbar", width = 0.8,
               na.rm = TRUE, fatten = 1, size = 0.3) +
  scale_color_manual(values = c("#ff6eff", "#3366ff"),
                     breaks = c("Female", "Male")) +
  ggbeeswarm::geom_beeswarm(size = 0.6, cex = 4.5, groupOnX = TRUE) +
  facet_wrap(~ sex, nrow = 1) +
  lims(y = c(-3, 0)) +
  labs(x = NULL,
       y = latex2exp::TeX("log$_2$(abundance)"),
       title = "CL(72:8)") +
  theme_minimal(base_size = 6) +
  theme(axis.text.x = element_text(color = "black", size = 5, angle = 90,
                                   vjust = 0.5, hjust = 1),
        axis.text.y = element_text(color = "black", size = 5),
        axis.title.y = element_text(color = "black", size = 6.5),
        plot.title = element_text(color = "black", size = 6.5),
        panel.grid = element_blank(),
        axis.ticks.y = element_line(color = "black", size = 0.3),
        axis.line = element_line(color = "black", size = 0.3),
        plot.background = element_rect(fill = "white",
                                       color = NA),
        legend.text = element_text(color = "black", size = 5),
        legend.title = element_text(color = "black", size = 5),
        strip.text = element_text(color = "black", size = 6.5))

cl

ggsave(file.path("..", "..", "plots", "METAB_cardiolipin.pdf"), cl,
       height = 1.4, width = 1.5, family = "ArialMT")

Tyler Sagendorf

01 May, 2024