🧬 Intro to Single-Cell Bioinformatics (Python)

This tutorial series introduces basic concepts in single-cell analysis using Python. All notebooks are designed to run in Google Colab.

Tutorial 1, 2, 3, 4

---

📚 Notebooks

1. tutorial-1 (Foundations)

• What is a DataFrame
• Rows vs columns
• Data types
• Basic data exploration

Tools: Scanpy

---

2. tutorial-2 (scRNA-seq with Scanpy)

• Intro to single-cell data in Python
• AnnData structure (.X, .obs, .var)
• UMAP visualization

Tools: Scanpy

---

3. tutorial-3 (TCR Analysis with Dandelion)

• Intro to single-cell TCR sequencing
• Contig annotation files
• AIRR format
• Clonotype network visualization

Tools: Scanpy, Dandelion, Scirpy

---

4. tutorial-4 (Deep Learning on TCRs)

• Train a model on TCR sequences (~10k)
• Use a pre-trained model
• Visualize embeddings

Tools: PyTorch

---

▶️ How to Use

• Open notebooks in Google Colab
• Run cells from top to bottom

---

🎯 Outcomes

By the end, you will:

• Understand DataFrames and AnnData
• Run a basic single-cell workflow
• Explore TCR data
• Apply deep learning to biological sequences

---

👥 Contributors

• Norman
• Linlin

---