# find overlaps between sigLRT_genes and sigOE
<- sigLRT_genes %>% subset(gene %in% sigOE$gene)
overlap_LRT_OE nrow(overlap_LRT_OE)
[1] 4510
Compare the resulting gene list from the LRT test to the gene lists from the Wald test comparisons.
How many of the sigLRT_genes
overlap with the significant genes in sigOE
?
# find overlaps between sigLRT_genes and sigOE
overlap_LRT_OE <- sigLRT_genes %>% subset(gene %in% sigOE$gene)
nrow(overlap_LRT_OE)
[1] 4510
How many of the sigLRT_genes
overlap with the significant genes in sigKD
?
---
title: "DGE analysis using LRT in DESeq2"
---
```{r 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.**
**How many of the `sigLRT_genes` overlap with the significant genes in `sigOE`?**
```{r}
# find overlaps between sigLRT_genes and sigOE
overlap_LRT_OE <- sigLRT_genes %>% subset(gene %in% sigOE$gene)
nrow(overlap_LRT_OE)
```
**How many of the `sigLRT_genes` overlap with the significant genes in `sigKD`?**
```{r}
# find overlaps between sigLRT_genes and sigKD
overlap_LRT_KD <- sigLRT_genes %>% subset(gene %in% sigKD$gene)
nrow(overlap_LRT_KD)
```