Identifying key modules that are responsible for intrinsic and extrinsic mechanisms of tumor development in tumor micro-environment (TME), from 21 mouse scRNA libraries.

📘 Project Overview

This project analyzes 21 single-nuclei RNA-seq samples across three tumor cell lines, each treated with either SOS or Veh treatments. The goal is to understand treatment effects on cell composition, tumor pathway activity, and tumor-specific gene expression patterns.

📊 Analysis Tasks

Task 1: Initial Processing and Broad Annotation

• QC, filtering, normalization, clustering
• Broad cell type annotation
• Cell type composition comparison across treatments and cell lines

Task 2: Tumor vs. Normal Cell Identification

• Quantifying the expression of YFP gene (The Yellow Florescence gene was introduced into the tumor cells, and its expression is used as a marker to identify and track tumor cells)
• Copy Number Variation Analysis (InferCNV)

Task 3: DEG and GO Enrichment in Epithelial Cells (how the genes are differentially expressed in response to the treatment at different cell line)

• DGE & GO Enrichment Analysis (at single cell level)
• DGE & GO Enrichment Analysis (pseudo bulk analysis)
• Finding DEGs overlap across 3 cell lines

Task 4: Pathway Scoring and Visualization on Epithelial/tumor cells

• Scoring of hallmark gene sets per cell
• Comparing the Pathway trends in tumor cells, across treatments in different cell lines

Task 5: COX Pathway Gene Expression in Epithelial cells

• Identifying the cells express the COX pathway genes (Ptges+, Ptgs1+, Ptgs2+ cells)
• Analyzing the co-expression of the genes, providing statistics and visualizations

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💡 Notes

• Raw data is not publicly available due to client ownership and confidentiality.
• Some example outputs plots are organized by task in the output/ folder.
• This project is designed for both reproducibility and clarity.

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📬 Contact

Author: Nasim Rahmatpour Email: nasimrahmatpour1@gmail.com GitHub: (https://github.com/nasimbio)