NCBI Sequence Analysis 🧬

This project is a beginner-friendly practice exercise for learning how to retrieve and analyze gene sequences using NCBI Entrez API and Biopython. It provides a hands-on experience in handling biological sequence data, making it ideal for those new to bioinformatics.

By following the included Jupyter Notebook, users can fetch genetic sequences, analyze nucleotide composition, and visualize results.

📌 What This Project Covers

• ✅ Retrieving a gene sequence from NCBI Entrez API
• ✅ Computing GC content of the sequence
• ✅ Counting nucleotide frequency (A, T, G, C)
• ✅ Saving results in FASTA and CSV formats
• ✅ Generating a nucleotide frequency bar chart

📂 Project Structure

📁 ncbi-seq-analysis  
 ├── 📝 `ncbi_sequence_analysis.ipynb`  *(Jupyter Notebook for interactive execution)*  
 ├── 🐍 `ncbi_sequence_analysis.py`  *(Python script for running in the terminal)*  
 ├── 📄 `base_counts.csv`  *(CSV file with nucleotide frequency data)*  
 ├── 🎨 `nucleotide_frequency.png`  *(Bar chart visualization of nucleotide composition)*  
 ├── 🧬 `hbb_gene.fasta`  *(FASTA file of the retrieved gene sequence)*  
 ├── 📄 `README.md`  *(Project documentation)*  

⏳ Estimated Time to Complete

This project should take 1 to 3 hours, depending on familiarity with Python and Jupyter Notebook.

🚀 How to Use

Instead of cloning the repository, it is recommended to manually follow the steps and write the code yourself to reinforce learning.

1️⃣ Set Up the Environment

conda create -n ncbi_seq_analysis python=3.10 -y
conda activate ncbi_seq_analysis
conda install -c conda-forge biopython pandas requests matplotlib -y

2️⃣ Open Jupyter Notebook

jupyter lab

Create a new notebook and refer to this README while writing and executing each block of code step by step.

3️⃣ Clone code

Type out line by line, run codes by blocks, troubleshoot if you meet one, google If you don't understand, and feel free to ask me!

📊 Example Output

Gene ID: NM_000518.5
Sequence length: 626 bp
GC Content: 53.66%
Nucleotide frequency:
A: 150 occurrences
T: 130 occurrences
G: 170 occurrences
C: 176 occurrences
Graph saved: nucleotide_frequency.png

✅ The nucleotide composition graph is also generated:

📌 Important: Before running the script, make sure to replace the email placeholder with your own in the Entrez API setup.

Entrez.email = "your_email@example.com"  # Replace with your actual email

This project is a great hands-on way to practice bioinformatics and sequence analysis! 🧬✨