RNASeq-Pasilla Analysis

Overview

Author: Daniel Scheuermann
Date: 2024-01-31

This repository contains a comprehensive R script and analysis to replicate a study conducted in 2010, which focused on the Pasilla gene using RNA-seq data. The Pasilla gene was depleted, and RNA was isolated to prepare single-end and paired-end libraries for treated vs untreated samples. The resulting libraries were sequenced to obtain RNA-seq data, and this script compares the gene expression in treated vs untreated samples.

Dependencies

Ensure you have the following R packages installed before running the script:

• DESeq2
• pheatmap
• dplyr
• RColorBrewer
• ggplot2
• ggrepel
• clusterProfiler
• goseq

RMD Sections

Please for RNASeq-Pasilla.rmd for a breakdown of the code and the exploration of the data resulting from each section.

1. Intro

Provides an overview of the study and its inspiration.

2. Data Setup

Reads and sets up the count data and sample information.

3. DESeq2 Setup

Creates the DESeq2 object and specifies treatment factors.

4. Data Manipulation

Filters genes and performs DESeq2 analysis.

5. Looking at Specific Genes

Examines specific genes, focusing on the Pasilla gene.

6. Data Manipulation 2

Filters differentially expressed genes.

7. Storing Results

Saves manipulated data and normalized counts to CSV files.

8. Visualization (Dispersion and PCA)

Generates dispersion and PCA plots for visualizing sample relationships.

9. Visualization (HeatMaps and Volcano)

Produces heatmaps, MA plots, and volcano plots for differential gene expression visualization.

10. GO-Analysis

Describes the results of Gene Ontology (GO) analysis.

11. Kegg Pathway Analysis

Summarizes the findings of Kegg pathway analysis.

12. Future Goals

Outlines the author's reflections and future goals for the project.

Sources

• Original Study
• DESeq2 Tutorial
• GO Enrichment Tutorial
• Kegg Pathway Analysis Tutorial
• Kegg Pathway Database