DNA Sequence Analysis Toolkit 🧬

This project is a Python application developed as part of the "Systems and Script Programming" module of the Master 1 Bioinformatics (USTHB). It provides a comprehensive toolkit for DNA sequence analysis, accessible via a graphical interface (GUI) or a command-line interface (CLI).

✨ Graphical Interface Screenshots

The application offers an intuitive user experience through its interface built with Tkinter. Main Menu: Analysis Window:

🚀 Features

The application allows performing a wide range of operations on DNA sequences, whether randomly generated or read from a file.

• Sequence Management:
  • Generate a random DNA string of a given length.
  • Load a DNA sequence from a file (.fasta, .txt, etc.).
  • Verify the validity of a sequence (contains only A, C, G, T).
• Fundamental Analyses:
  • Base frequency: Calculate the number of occurrences of each nucleotide (A, C, G, T).
  • GC content: Calculate the percentage of G and C bases in the sequence.
  • Transcription: Convert a DNA sequence to its corresponding RNA.
  • Translation: Translate an RNA sequence to its protein sequence (amino acids).
  • Reverse Complement: Generate the reverse complementary sequence.
  • Codon frequency: Calculate the frequency of each three-nucleotide codon.
• Advanced Features:
  • Point Mutation: Introduce a specified number of mutations by substitution.
  • Motif Search: Find all occurrences of a sub-motif in the sequence.
  • Consensus Sequence: From a set of sequences, generate the profile matrix and consensus DNA string.
• Utility:
  • Save analysis history and results to a text file.

🔧 How to Use

1. Clone this repository:

   git clone https://github.com/YOUR_USERNAME/DNA-Sequence-Analyzer.git
   cd DNA-Sequence-Analyzer

2. (Optional but recommended) Create a virtual environment:

   python -m venv env
   # On Windows
   .\env\Scripts\activate
   # On macOS/Linux
   source env/bin/activate

3. Install required dependencies:

   pip install -r requirements.txt

4. Launch the application of your choice:
   • For the graphical interface (GUI):

     python App.py

   • For the command-line interface (CLI):

     python Menu.py

📂 Project Structure

The code is organized modularly for better readability and maintenance:

• App.py: Entry point for the graphical application (Tkinter).
• Menu.py: Entry point for the command-line application.
• ADN_*.py, Count_*.py, etc.: Modules each containing a specific bioinformatics function.
• /assets: Contains images used by the graphical interface.
• /sample_data: Contains example sequence files.
• enonce_projet.pdf: The original document describing the project.