---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 librarieslibrary(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 celltypemeta_sub <- seurat_sub@meta.datameta_sub$celltype <-factor(meta_sub$celltype)meta_sub$condition_sample <-paste0(meta_sub$condition, "_", meta_sub$sample)# Run differential proportion analysispropres <-propeller(seurat_sub, sample=seurat_sub$sample,clusters = seurat_sub$celltype,group = seurat_sub$condition)props <-getTransformedProps(meta_sub$celltype, meta_sub$condition_sample, transform="logit")props_df <- props$Proportions %>%as.data.frame() %>%mutate(condition =str_split_i(sample, "_", 1))props_df_summary <- props_df %>%group_by(clusters, condition) %>%summarise(mean =mean(Freq), sd =sd(Freq))```# Exercise 11. Take a look at the results table `propres`. Which celltypes show a significant change in composition between TN and cold7?2. Does this line up with what we observed in the counts table?```{r}propres``````{r}## Check count numbers of cellsmeta_sub$condition_sample <-paste0(meta_sub$condition, "_", meta_sub$sample)table(meta_sub$condition_sample, meta_sub$celltype)```