PCA and UMAP analysis of RNA-seq datasets

A simple analysis of bulk RNA-seq and scRNA-seq datasets using PCA and UMAP.
The project focuses on QC, visualization, clustering, and interpretation of biological replicates and groups.

Datasets

• Bulk RNA-seq: HL-60 cell line — GSE184891
• scRNA-seq: AML patient samples — GSE116256

Goals

• Perform QC analysis on bulk RNA-seq data using PCA
• Check consistency of biological replicates
• Cluster scRNA-seq data using UMAP
• Identify differences between cell groups

Methods

• PCA via scikit-learn
• UMAP and clustering via scanpy
• Visualization using matplotlib and seaborn

How to Run

1. Install dependencies:

   pip install -r requirements.txt

2. Launch the notebook:

   jupyter notebook Practice_PCA_bulk_RNA_seq_scRNA_seq.ipynb

License

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