Version Compatibility

Reference examples tested with: BioPython 1.83+, numpy 1.26+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

MSA Statistics

Calculate sequence identity, conservation scores, substitution counts, and other alignment metrics.

Required Import

Goal: Load modules for alignment I/O, substitution scoring, and statistical calculations.

Approach: Import AlignIO for reading alignments, Counter for column analysis, numpy for matrix operations, and math for entropy calculations.

from Bio import AlignIO
from Bio.Align import substitution_matrices
from collections import Counter
import numpy as np
import math

Pairwise Identity

"Calculate percent identity" → Compute the fraction of identical aligned residues between sequence pairs.

Goal: Measure sequence similarity as percent identity for individual pairs or across all sequences in an alignment.

Approach: Count matching non-gap positions divided by total aligned positions; optionally compute a full N-by-N identity matrix.

Calculate Identity Between Two Sequences

def pairwise_identity(seq1, seq2):
    matches = sum(a == b and a != '-' for a, b in zip(seq1, seq2))
    aligned_positions = sum(a != '-' or b != '-' for a, b in zip(seq1, seq2))
    return matches / aligned_positions if aligned_positions > 0 else 0

alignment = AlignIO.read('alignment.fasta', 'fasta')
seq1, seq2 = str(alignment[0].seq), str(alignment[1].seq)
identity = pairwise_identity(seq1, seq2)
print(f'Identity: {identity * 100:.1f}%')