BunyaminMSA 1.0.0

Pure Python Clustal Omega Multiple Sequence Alignment implementation

BunyaminMSA

Pure Python implementation of the Clustal Omega Multiple Sequence Alignment (MSA) algorithm.

Bioinformatics Final Project — Bunyamin Arpc

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Installation

pip install BunyaminMSA

Or from source:

git clone https://github.com/bunyaminarpc/BunyaminMSA.git
cd BunyaminMSA
pip install -e .

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Quick Start

from bunyaminmsa import ClustalOmega

msa = ClustalOmega()

sequences = ["ACGTACGT", "ACGGACGT", "TTTTACGT"]
names     = ["Human", "Mouse", "Zebrafish"]

result = msa.align(sequences, names=names)
print(result["alignment_str"])

FASTA Input

fasta = """
>seq1
ACGTACGTACGT
>seq2
ACGGACGTACGG
>seq3
TTTTACGTATTT
"""
result = msa.align_from_fasta(fasta)

Command Line

bunyaminmsa --fasta input.fasta
bunyaminmsa --seqs ACGT ACGG TTTT --names s1 s2 s3
bunyaminmsa --fasta input.fasta --output alignment.aln

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Algorithm Overview

Clustal Omega performs MSA in three main stages:

1. Pairwise Distance Calculation (k-mer based)

All sequence pairs are compared using k-mer frequency profiles and cosine distance. This is faster than full pairwise DP and robust to long sequences.

2. Guide Tree Construction (UPGMA)

The pairwise distance matrix is used to build a binary guide tree using UPGMA (Unweighted Pair Group Method with Arithmetic mean). Closely related sequences are merged first.

3. Progressive Alignment

Sequences are aligned following the guide tree (post-order traversal):

• Leaf–Leaf: Needleman-Wunsch global alignment with affine gap penalties
• Profile–Profile: Frequency profiles are built for each aligned group; alignment proceeds between profiles column-by-column

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API Reference

ClustalOmega

Method	Description
align(sequences, names=None)	Align list of sequences
align_from_fasta(fasta_text)	Parse FASTA string and align
get_distance_matrix()	Return last computed distance matrix
get_guide_tree()	Return last computed guide tree

Result Dictionary

Key	Type	Description
names	list[str]	Sequence names
aligned	list[str]	Aligned sequences (with gaps)
alignment_str	str	CLUSTAL-format alignment
distance_matrix	list[list[float]]	n×n pairwise distances
sequence_type	str	'dna' or 'protein'
guide_tree	str	String representation of UPGMA tree

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Running Tests

python tests/test_clustal_omega.py
# or
pytest tests/

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License

MIT License — Bunyamin Arpc