SD_2301

setup

library(tidyverse)

── Attaching core tidyverse packages ──── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(janitor)

Attaching package: 'janitor'

The following objects are masked from 'package:stats':

    chisq.test, fisher.test

library(readxl)
library(here)

here() starts at /Users/peterhiggins/Documents/RCode/SD_2301

library(ggsignif)

Read in data

df <- read_excel(here("SD2301_tidy.xlsx")) |> 
  select(mice, category, TNF:STAT3) |>
  pivot_longer(cols = !c(mice,category), names_to = "transcript", values_to = "value") |>
  mutate(arm = case_when(
    category == 1 ~ "Negative Control",
    category == 2 ~ "Drug Control",
    category == 3 ~ "Inflamm",
    category == 4 ~ "Inflamm & SD3",
    category == 5 ~ "Inflamm & SD")) |> 
  mutate(transcript = case_when(
    transcript == "TNF" ~ "TNFa",
    transcript == "IL1" ~ "IL-1b",
    transcript == "IL6" ~ "IL-6",
    transcript == "STAT3" ~ "STAT3",
    transcript == "TGF" ~ "TGFb",
    transcript == "INF" ~ "IFNg",
    transcript == "il10" ~ "IL-10")) |>  
    mutate(arm = ordered(arm, levels = c("Negative Control", "Drug Control", "Inflamm", "Inflamm & SD3", "Inflamm & SD"))) |> 
  mutate(transcript = factor(transcript, levels = c("TNFa", "IL-1b", "IL-6", "IFNg", "TGFb", "STAT3", 'IL-10'))) |> 
  filter(transcript != "TGFb" & transcript != "STAT3") |> 
  filter(arm != "Inflamm & SD3") |>
  filter(!is.na(value))

Analysis Code

plot <- df |> 
  filter(arm != "Inflammation & SD3") |> 
  ggplot(aes(x = arm, y = value, fill = arm)) +
  geom_boxplot() +
  geom_point(position = position_jitterdodge(), size = 1.5, alpha = 0.5) +
  facet_wrap(~transcript, scales = "free_y") +
  scale_fill_manual(values = c("Negative Control" = "white", "Drug Control" = "gray", "Inflamm" = "red", "Inflamm & SD" = "yellow")) +
    theme_classic(base_size = 14) +
  theme(legend.position = "none") +
  scale_x_discrete(guide = guide_axis(n.dodge = 2))

plot

ggsave(plot, filename = here("SD2301_plot.png"), width = 12, height = 8, dpi = 300)