DGE analysis using LRT in DESeq2 - Answer Key

Author

Will Gammerdinger

Published

November 13, 2025

Exercise 1

Compare the resulting gene list from the LRT test to the gene lists from the Wald test comparisons.

1. How many of the sigLRT_genes overlap with the significant genes in sigOE?

# Find overlaps between sigLRT_genes and sigOE
overlap_LRT_OE <- sigLRT_genes %>% subset(gene %in% sigOE$gene)
nrow(overlap_LRT_OE)

[1] 4510

2. How many of the sigLRT_genes overlap with the significant genes in sigKD?

# Find overlaps between sigLRT_genes and sigKD
overlap_LRT_KD <- sigLRT_genes %>% subset(gene %in% sigKD$gene)
nrow(overlap_LRT_KD)

[1] 2741

Reuse

CC-BY-4.0

---
title: "DGE analysis using LRT in DESeq2 - Answer Key"
author:
  - Will Gammerdinger
date: "2025-11-13"
license: "CC-BY-4.0"
editor_options: 
  markdown: 
    wrap: 72
---

```{r}
#| label: data_setup
#| echo: false

# load libraries needed to render this lesson
library(tidyverse)
library(DESeq2)

# load objects needed to render this lesson
dds_lrt <- readRDS("data/intermediate_dds_lrt.RDS")
sigOE   <- readRDS("data/intermediate_res_sigOE.RDS")
sigKD   <- readRDS("data/intermediate_res_sigKD.RDS")
padj.cutoff <- 0.05

# Extract results for LRT
res_LRT <- results(dds_lrt)
# Create a tibble for LRT results
res_LRT_tb <- res_LRT %>%
  data.frame() %>%
  rownames_to_column(var="gene") %>% 
  as_tibble()
# Subset to return genes with padj < 0.05
sigLRT_genes <- res_LRT_tb %>% 
  dplyr::filter(padj < padj.cutoff)
```

# Exercise 1

**Compare the resulting gene list from the LRT test to the gene lists from the Wald test comparisons.**

**1. How many of the `sigLRT_genes` overlap with the significant genes in `sigOE`?**

```{r}
#| label: overlap_LRT_OE
# Find overlaps between sigLRT_genes and sigOE
overlap_LRT_OE <- sigLRT_genes %>% subset(gene %in% sigOE$gene)
nrow(overlap_LRT_OE)
```

**2. How many of the `sigLRT_genes` overlap with the significant genes in `sigKD`?**

```{r}
#| label: overlap_LRT_KD
# Find overlaps between sigLRT_genes and sigKD
overlap_LRT_KD <- sigLRT_genes %>% subset(gene %in% sigKD$gene)
nrow(overlap_LRT_KD)
```