Microarray Analysis Pipeline - Shiny Interface Overview The Microarray Analysis Pipeline is a Shiny-based web application that provides an interactive interface for analyzing microarray data. It allows users to: • Upload CEL files and assign sample groups • Perform quality control (QC) analysis with various plots • Run differential expression analysis and visualize results • Download results for further analysis This pipeline is designed to simplify the microarray data analysis process for researchers and bioinformaticians.
Features • Data Upload: Supports uploading multiple CEL files and assigning experimental groups. • Quality Control: Generates RNA degradation plots, boxplots, MA plots, and density plots. • Differential Expression Analysis: Displays results in a table format and provides interactive volcano plots and heatmaps. • Downloadable Results: Users can download processed data and analysis results in CSV format. • User-Friendly Interface: Built using Shiny and Shiny Dashboard, making it accessible via a web browser.
Installation & Dependencies The application requires R and several Bioconductor and CRAN packages. Required R Packages The following packages are installed automatically if they are missing: • shiny • shinydashboard • DT • plotly Ensure you have Bioconductor installed before running the application. To install dependencies manually, run: if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
required_packages <- c("shinydashboard", "DT", "plotly")
for (package in required_packages) { if (!requireNamespace(package, quietly = TRUE)) BiocManager::install(package) }
How to Run the Application
- Install dependencies (if not already installed).
- Ensure the script microarray_pipeline.R is in the same directory as app.R.
- Open R and set the working directory to the folder containing the app.
- Run the following command in R:
- library(shiny)
- runApp("app.R")
- The application will launch in your default web browser.
Usage Guide 1️. Upload Data • Click on the "Upload Data" tab. • Upload your CEL files (raw microarray data). • Assign groups (e.g., control vs. treatment). • Specify an output directory. • Click "Run Analysis" to start the pipeline. 2️. Quality Control • Navigate to the "Quality Control" tab. • View diagnostic plots such as: o RNA degradation plots o Box plots o MA plots o Density plots 3️. View and Download Results • Go to the "Analysis Results" tab. • Select a comparison and view: o Differential expression table o Volcano plot o Heatmap of top 25 differentially expressed genes • Download the results as a CSV file.
File Structure 📂 Microarray-Analysis-Pipeline │-- 📄 app.R # Main Shiny app │-- 📄 microarray_pipeline.R # Core microarray analysis functions │-- 📁 data/ # (Optional) Example dataset │-- 📁 microarray_results/ # Output directory (generated after running analysis)
Troubleshooting • Application doesn't launch? o Ensure you have installed all dependencies. o Run sessionInfo() in R to check for missing packages. • No results appear after clicking "Run Analysis"? o Verify that your CEL files are correctly uploaded and groups are assigned. o Check if microarray_pipeline.R is present in the directory. • Plots not displaying properly? o Ensure you have plotly installed correctly using install.packages("plotly").