arman-bio-msa 0.1.0

Simple Multiple Sequence Alignment using Needleman-Wunsch Dynamic Programming

arman-bio-msa

Simple Multiple Sequence Alignment using Needleman-Wunsch Dynamic Programming.

Student Number: 221201931
Algorithm Assignment: 221201931 % 4 = 3 → Dynamic Programming

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Why Dynamic Programming?

Each student is assigned an algorithm based on student_number % 4. Since 221201931 % 4 = 3, the assigned algorithm is Dynamic Programming.

This package implements the Needleman-Wunsch algorithm, which is the most well-known dynamic programming method for sequence alignment in bioinformatics.

What is Multiple Sequence Alignment?

Multiple Sequence Alignment (MSA) means lining up three or more biological sequences (DNA, RNA, or protein) so that similar characters appear in the same column. Gaps (-) are inserted where needed. This helps scientists find evolutionary relationships and important regions across species.

What is Needleman-Wunsch?

Needleman-Wunsch is a dynamic programming algorithm that finds the optimal global alignment between two sequences. It works in three steps:

1. Initialize a score matrix with gap penalties
2. Fill each cell by choosing the best of three options (diagonal, up, left)
3. Traceback from the bottom-right corner to build the aligned sequences

For multiple sequences, this package uses progressive alignment: align the first two sequences, then add each remaining sequence one by one.

Scoring System

Event	Score
Match	+1
Mismatch	-1
Gap	-2

Scores are customizable via function parameters.

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Installation

Install from PyPI (after publishing):

pip install arman-bio-msa

Install from TestPyPI:

pip install -i https://test.pypi.org/simple/ arman-bio-msa

Install locally for development:

git clone https://github.com/armanshafiee/arman-bio-msa.git
cd arman-bio-msa
pip install -e .

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Usage

Run the demo:

python main.py

Use in your own code:

from bio_msa import needleman_wunsch, multiple_alignment

# Pairwise alignment
matrix, aligned1, aligned2 = needleman_wunsch("AGCTG", "ACGTG")
print(aligned1)  # AGCTG
print(aligned2)  # ACGTG

# Multiple alignment
sequences = ["AGCTG", "ACGTG", "AGTC"]
result = multiple_alignment(sequences)
for seq in result:
    print(seq)

Custom scoring:

matrix, a1, a2 = needleman_wunsch("ATCG", "ACG", match=2, mismatch=-1, gap=-3)

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Example Output

Input Sequences:
  Seq1: AGCTG
  Seq2: ACGTG
  Seq3: AGTC

FINAL MULTIPLE ALIGNMENT
  Seq1: AGCTG
  Seq2: ACGTG
  Seq3: AG-TC

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Building and Publishing to PyPI

Step 1: Install build tools

python -m pip install --upgrade build twine

Step 2: Build the package

python -m build

This creates files in the dist/ folder.

Step 3: Upload to TestPyPI (for testing)

python -m twine upload --repository testpypi dist/*

Step 4: Test installation from TestPyPI

pip install -i https://test.pypi.org/simple/ arman-bio-msa

Step 5: Upload to real PyPI

python -m twine upload dist/*

Step 6: Install from PyPI

pip install arman-bio-msa

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Project Structure

arman-bio-msa/
├── bio_msa/
│   ├── __init__.py        # Package exports
│   └── aligner.py         # Needleman-Wunsch algorithm
├── examples/
│   └── example_usage.py   # Usage examples
├── main.py                # Run the demo
├── pyproject.toml         # PyPI package config
├── README.md              # This file
├── report_draft.md        # Project report
├── LICENSE                # MIT License
└── .gitignore

License

MIT License - see LICENSE for details.