Step 6: Visualize the Top Differentially Expressed Genes and their Functions

Using the table of annotated differentially expressed genes (generated in step 5), make some insightful data visualizations to understand the differing key biological processes between coral embryos and coral recruits

Author

Sarah Tanja

Published

May 30, 2023

Install Packages

if ("tidyverse" %in% rownames(installed.packages()) == 'FALSE') install.packages('tidyverse')
if ("ggplot2" %in% rownames(installed.packages()) == 'FALSE') install.packages('ggplot2')

Load Libraries

library(tidyverse)
library(ggplot2)

Read in Data

annote_DEG <- read.delim(file = "../output/annote_DEGlist.tab", sep = " ", header = TRUE)
head(annote_DEG)

# Select top 20 differentially expressed genes
deseq2.res <- results(deseq2.dds)
res_ordered <- deseq2.res[order(deseq2.res$padj), ]
#create object that we will reference later
top_genes <- row.names(res_ordered)[1:20]

knitr::kable(
  mtcars[1:3, 1:3]
)

knitr::kable(
  top_genes
)

---
title: "Step 6: Visualize the Top Differentially Expressed Genes and their Functions"
subtitle: "Using the table of annotated differentially expressed genes **(generated in step 5)**, make some insightful data visualizations to understand the differing key biological processes between coral embryos and coral recruits"
author: "Sarah Tanja"
date: "`r format(Sys.time(), '%d %B, %Y')`"
format:
  html:
    df-print: paged
    toc: true
    toc-location: left
    smooth-scroll: true
    link-external-icon: true
    link-external-newwindow: true
    code-fold: false
    code-tools: true
    code-copy: true
    highlight-style: breeze
    code-overflow: wrap
    theme: minty
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  echo = TRUE,         # Display code chunks
  eval = FALSE,        # Evaluate code chunks
  warning = FALSE,     # Hide warnings
  message = FALSE,     # Hide messages
  fig.width = 6,       # Set plot width in inches
  fig.height = 4,      # Set plot height in inches
  fig.align = "center" # Align plots to the center
)
```

### Install Packages

```{r install packages, filename='r'}
if ("tidyverse" %in% rownames(installed.packages()) == 'FALSE') install.packages('tidyverse')
if ("ggplot2" %in% rownames(installed.packages()) == 'FALSE') install.packages('ggplot2')
```

### Load Libraries

```{r load libraries, filename='r'}
library(tidyverse)
library(ggplot2)
```

### Read in Data

```{r, filename='r'}
annote_DEG <- read.delim(file = "../output/annote_DEGlist.tab", sep = " ", header = TRUE)
head(annote_DEG)
```

```{r, filename='r'}
# Select top 20 differentially expressed genes
deseq2.res <- results(deseq2.dds)
res_ordered <- deseq2.res[order(deseq2.res$padj), ]
#create object that we will reference later
top_genes <- row.names(res_ordered)[1:20] 
```

```{r}
#| column: margin

knitr::kable(
  mtcars[1:3, 1:3]
)
```

```{r}
#| column: margin

knitr::kable(
  top_genes
)

```