README: DNA Microarray Data Analysis with Bioconductor and R

This repository contains the R code and data files for analyzing DNA microarray data using Bioconductor and R. The project is based on the example provided in Chapter 16 of the Limma User Guide and focuses on the "Swirl Zebrafish" experiment, which investigates differential gene expression between mutant and wild-type zebrafish.

Project Overview

The primary goal of this project is to:

• Perform genome-wide analyses of differentially expressed genes.
• Use permutation distributions and False Discovery Rate (FDR) corrections.
• Generate visualizations to interpret the data and analysis results.

The repository includes:

• R Markdown file (DNA_Microarray_Analysis.Rmd) with detailed analysis steps and visualizations.
• Data files necessary to replicate the analysis.

Key Features

1. Data Preprocessing:

   • Reads and inspects raw data files (e.g., targets and GAL files).
   • Creates image plots of background intensities and raw M-values.

2. Normalization:

   • Implements within-array normalization using "printtiploess."
   • Applies scale normalization across arrays as recommended by the Limma User Guide.

3. Linear Modeling and Statistical Analysis:

   • Fits a linear model to the normalized data.
   • Applies empirical Bayes moderation to improve statistical reliability.
   • Identifies differentially expressed genes.

4. FDR Estimation:

   • Compares results from Limma's FDR estimation with other methods using the FDRestimation package.

5. Visualizations:

   • MA-plots, boxplots, volcano plots, and image plots for data interpretation.
   • Effect of empirical Bayes moderation visualized through scatter plots.

Getting Started

Prerequisites

Ensure you have the following R packages installed:

• limma
• knitr
• ggokabeito
• tidyverse
• FDRestimation

Folder Structure

repo/
├── data/                  # Contains raw data files (e.g., SwirlSample.txt, fish.gal)
├── DNA_Microarray_Analysis.Rmd  # R Markdown file for analysis
└── README.md              # Project documentation

Running the Analysis

1. Open terminal.
2. Clone this repository: git clone https://github.com/shussin245/DNA-Microarray-Limma.git
3. cd DNA-Microarray-Limma
4. Open the DNA_Microarray_Analysis.Rmd file in RStudio.
5. Run the analysis by knitting the R Markdown file to the desired output format (HTML, PDF, Word).

Results

The results include:

• Normalized gene expression data.
• Lists of significant genes with adjusted p-values.
• Visualizations to assess data quality and normalization effects.

References

1. Smyth, G. K. (2005). Limma: Linear models for microarray data. In Bioinformatics and Computational Biology Solutions Using R and Bioconductor (pp. 397-420). Springer.
2. Limma User Guide.

Acknowledgments

Special thanks to the Bioconductor community and the authors of the Limma User Guide for providing the foundation for this analysis.