Summarizing results from the Wald test - Answer key

Exercise 1

MOV10 Differential Expression Analysis: Control versus Knockdown

Using the same p-adjusted threshold as above (padj.cutoff < 0.05), subset res_tableKD to report the number of genes that are up- and down-regulated in Mov10_knockdown compared to control.

# Create a tibble of results
res_tableKD_tb <- res_tableKD %>%
  data.frame() %>%
  rownames_to_column(var="gene") %>% 
  as_tibble()

How many genes are differentially expressed in the Knockdown compared to Control? How does this compare to the overexpression significant gene list (in terms of numbers)?

# Subset the tibble to keep only significant genes
sigKD <- res_tableKD_tb %>%
  dplyr::filter(padj < padj.cutoff)

There are rnrow(sigKD) genes differentially expressed in the Knockdown compared to Control, and 4774 genes differentially expressed in the Overexpression compared to Control. Therefore, fewer genes are present in the Knockdown significant gene list.

---
title: "Summarizing results from the Wald test - Answer key"
---

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

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

# load objects needed to render this lesson
res_tableOE <- readRDS("./data/intermediate_res_tableOE.RDS")
res_tableKD <- readRDS("./data/intermediate_res_tableKD.RDS")
padj.cutoff <- 0.05

# Create a tibble of results
res_tableOE_tb <- res_tableOE %>%
  data.frame() %>%
  rownames_to_column(var="gene") %>% 
  as_tibble()
# Subset the tibble to keep only significant genes
sigOE <- res_tableOE_tb %>%
  dplyr::filter(padj < padj.cutoff)
```

# Exercise 1

**MOV10 Differential Expression Analysis: Control versus Knockdown**

**Using the same p-adjusted threshold as above (`padj.cutoff < 0.05`), subset `res_tableKD` to report the number of genes that are up- and down-regulated in Mov10_knockdown compared to control.**

```{r}
# Create a tibble of results
res_tableKD_tb <- res_tableKD %>%
  data.frame() %>%
  rownames_to_column(var="gene") %>% 
  as_tibble()
```

**How many genes are differentially expressed in the Knockdown compared to Control? How does this compare to the overexpression significant gene list (in terms of numbers)?**

```{r}
# Subset the tibble to keep only significant genes
sigKD <- res_tableKD_tb %>%
  dplyr::filter(padj < padj.cutoff)
```

There are `rnrow(sigKD)` genes differentially expressed in the Knockdown compared to Control, and `r nrow(sigOE)` genes differentially expressed in the Overexpression compared to Control. Therefore, fewer genes are present in the Knockdown significant gene list.