Shiny Apps for RNA and scRNA-seq Analysis

This repository contains two interactive Shiny applications developed for RNA-seq and single-cell RNA-seq (scRNA-seq) data analysis. Each app is built to help researchers explore, analyze, and visualize transcriptomic datasets through a user-friendly browser interface without requiring advanced coding skills.

Contents

• RNA-seq_analysis_app/ – Differential expression analysis and visualization of bulk RNA-seq data
• scRNA-seq_analysis_app/ – End-to-end single-cell RNA-seq analysis using Seurat and related tools

📦 RNA-seq Analysis Shiny App

An interactive Shiny application for exploring and analyzing RNA-seq count data, supporting human, mouse, and rat datasets.

Key Features

• Data Upload: Accepts raw count data and metadata (CSV/TSV/space/semicolon-separated)
• Species Selection: Analyze datasets from human, mouse, or rat
• Exploratory Data Analysis: Visualize expression distributions, PCA plots, and sample clustering
• Differential Expression: Identify differentially expressed genes using DESeq2
• Custom Visualizations: Generate heatmaps, volcano plots, and boxplots

Installation

Requirements

• R (v4.4.1 or later)
• Required packages:

  install.packages(c("shiny", "ggplot2", "dplyr", "plotly"))
  if (!requireNamespace("BiocManager", quietly = TRUE))
      install.packages("BiocManager")
  BiocManager::install("DESeq2")

Running the App

git clone https://github.com/iichelhadi/Shiny_apps.git
cd Shiny_apps/RNA-seq_analysis_app

shiny::runApp("app.R")

🔬 scRNA-seq Analysis Shiny App

An interactive Shiny app for analyzing single-cell RNA-seq datasets, using the Seurat framework, scDblFinder, SingleR, and other tools.

Key features include:

• 10X Genomics data import
• Quality control filtering
• Doublet detection with scDblFinder
• Dimensionality reduction (PCA, UMAP)
• Clustering and cell type annotation
• Marker gene identification and visualization

For full documentation, visit: scRNA-seq_analysis_app/readme.md

💬 Contact

For questions, suggestions, or contributions:

Elhadi Iich 📧 iichelhadi@gmail.com 🌐 GitHub Profile

📄 License

This repository is licensed under the MIT License. See the LICENSE file for details.