sequenceCleaning

Insulin Sequence Processing

This project is a simple Python exercise for practicing text processing, file handling, and validation logic.

📋 Overview

The script performs the following tasks:

1. Reads the raw preproinsulin sequence from a text file.
2. Cleans the sequence by removing all non-letter characters and converting it to lowercase.
3. Splits the cleaned sequence into parts:
   • Signal peptide (24 amino acids)
   • B chain (30 amino acids)
   • C peptide (35 amino acids)
   • A chain (21 amino acids)
4. Saves each part to its own file.
5. Validates that each file has the correct length.

How to Run

1. Place the raw sequence file named preproinsulin-seq.txt in the same directory as the script.

2. Run the script:

python analyze-insulin.py

3. Check the output files:

   • preproinsulin-seq-clean.txt
   • lsinsulin-seq-clean.txt
   • binsulin-seq-clean.txt
   • cinsulin-seq-clean.txt
   • ainsulin-seq-clean.txt

4. Review the console output to confirm validation results.

Requirements

• Python 3.x
• No additional libraries required (only re from Python standard library).

Example Output

Cleaned sequence: 116 characters
lsinsulin-seq-clean.txt saved with 24 characters.
binsulin-seq-clean.txt saved with 30 characters.
cinsulin-seq-clean.txt saved with 35 characters.
ainsulin-seq-clean.txt saved with 21 characters.

=== Validation ===
❌ preproinsulin-seq-clean.txt: ERROR! 116/110 characters
✅ lsinsulin-seq-clean.txt: OK! 24/24 characters
✅ binsulin-seq-clean.txt: OK! 30/30 characters
✅ cinsulin-seq-clean.txt: OK! 35/35 characters
✅ ainsulin-seq-clean.txt: OK! 21/21 characters

⚠️ Note: If the cleaned sequence has more than 110 characters, review the raw input file for extra or invalid characters.

Key Concepts Practiced

• Regular expressions for data cleaning.
• String slicing to extract subsequences.
• File operations: reading, writing, validating.
• Error handling with try-except.

Author

Ícaro Torres — Software development student, always learning and improving Python skills.