Set-up DESeq2 analysis - Answer Key

Author

Will Gammerdinger, Noor Sohail

Published

September 5, 2025

Exercise 1

Take a look at the results table propres. Which celltypes show a significant change in composition between TN and cold7?
Does this line up with what we observed in the counts table?

---
title: "Set-up DESeq2 analysis - Answer Key"
authors: "Will Gammerdinger, Noor Sohail"
date: "Friday, September 5, 2025"
editor_options: 
  markdown: 
    wrap: 72
---

```{r}
#| label: load_data_libraries
#| echo: false
# Load libraries
library(Seurat)
library(DT)
library(tidyverse)
library(speckle)
library(sccomp)

seurat <- readRDS("data/BAT_GSE160585_final.rds")
seurat_sub <- subset(seurat, subset = (condition %in% c("TN", "cold7")))

# Create metadata df and factor celltype
meta_sub <- seurat_sub@meta.data
meta_sub$celltype <- factor(meta_sub$celltype)
meta_sub$condition_sample <- paste0(meta_sub$condition, "_", meta_sub$sample)

# Run differential proportion analysis
propres <- propeller(seurat_sub, 
                     sample=seurat_sub$sample,
                     clusters = seurat_sub$celltype,
                     group = seurat_sub$condition)

props <- getTransformedProps(meta_sub$celltype, 
                                 meta_sub$condition_sample, 
                                 transform="logit")

props_df <- props$Proportions %>%
  as.data.frame() %>%
  mutate(condition = str_split_i(sample, "_", 1))

props_df_summary <- props_df %>%
  group_by(clusters, condition) %>% 
  summarise(mean = mean(Freq), sd = sd(Freq))
```

# Exercise 1

1. Take a look at the results table `propres`. Which celltypes show a significant change in composition between TN and cold7?

2. Does this line up with what we observed in the counts table?