scRNA-seq Analysis Pipeline

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Table of Contents

• Overview
• Folder Structure
• Main Scripts
• Usage
• Output
• License
• Author

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🧬 Overview

This repository contains a comprehensive pipeline for single-cell RNA sequencing (scRNA-seq) analysis using R and Seurat. The workflow covers:

• Quality control
• Clustering
• Cell type annotation
• Trajectory analysis
• Differential expression
• Enrichment analysis

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📁 Folder Structure

Folder	Description
code/	R scripts for each analysis step
figure/	Output figures and plots

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📝 Main Scripts

Script	Purpose
scRNA_run.R	Main pipeline for preprocessing & clustering
marker_analysis.R	Marker gene identification & visualization
cell_annotation.R	Automated cell type annotation
trajectory_analysis.R	Trajectory & pseudotime analysis
differential_expression.R	Differential expression analysis
enrichment_analysis.R	Gene set enrichment & GO analysis

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🚀 Usage

1. Install required R packages:

• All required packages are listed in requirements.txt.
• You can install them manually or use the following R commands:

  pkgs <- readLines("requirements.txt")
  install.packages(pkgs[!pkgs %in% c("SingleR", "celldex", "monocle3", "clusterProfiler", "org.Hs.eg.db", "enrichplot", "msigdbr", "BiocManager")])
  if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")
  BiocManager::install(pkgs[pkgs %in% c("SingleR", "celldex", "monocle3", "clusterProfiler", "org.Hs.eg.db", "enrichplot", "msigdbr")])

2. Run scripts in order as described above.
3. Output files (.csv, .pdf, plots) are saved in the respective folders.

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📊 Output

• Cluster markers
• Cell type annotations
• Trajectory plots
• Differential expression results
• Enrichment analysis tables and figures

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📄 License

This project is licensed under the MIT License.

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👤 Author

Prokash21