Identifying key modules that are responsible for intrinsic and extrinsic mechanisms of tumor development in tumor micro-environment (TME), from 21 mouse scRNA libraries.
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.
- QC, filtering, normalization, clustering
- Broad cell type annotation
- Cell type composition comparison across treatments and cell lines
- 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
- Scoring of hallmark gene sets per cell
- Comparing the Pathway trends in tumor cells, across treatments in different cell lines
- Identifying the cells express the COX pathway genes (Ptges+, Ptgs1+, Ptgs2+ cells)
- Analyzing the co-expression of the genes, providing statistics and visualizations
- 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.
Author: Nasim Rahmatpour Email: nasimrahmatpour1@gmail.com GitHub: (https://github.com/nasimbio)