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Pairwise Alignment - Usage Guide

Overview

This skill performs pairwise sequence alignment to compare two DNA, RNA, or protein sequences. It uses Biopython's PairwiseAligner class which implements dynamic programming algorithms for finding optimal alignments.

Prerequisites

pip install biopython

Quick Start

Tell your AI agent what you want to do:

  • "Align these two DNA sequences and show me the best alignment"
  • "Compare this protein sequence against a reference using BLOSUM62"
  • "Find the best matching region between these two sequences"

Example Prompts

Global Alignment

"Perform a global alignment between ACCGGTAACGTAG and ACCGTTAACGAAG"

"Align the first two sequences in my FASTA file"

Local Alignment

"Find the best local alignment between these sequences to identify conserved regions"

"Use Smith-Waterman to find matching regions in these proteins"

Protein Alignment

"Align these two protein sequences using BLOSUM62 scoring"

"Compare my query protein against the reference with appropriate gap penalties"

Scoring and Analysis

"Calculate the alignment score between these sequences"

"Show me all optimal alignments and their scores"

What the Agent Will Do

  1. Create a PairwiseAligner with appropriate settings
  2. Configure scoring (match/mismatch for DNA, substitution matrix for proteins)
  3. Set gap penalties based on sequence type
  4. Generate optimal alignment(s)
  5. Display aligned sequences with match indicators
  6. Report alignment score and statistics

Supported Alignment Modes

Mode Best For
Global Full-length sequence comparison
Local Finding conserved regions
Semiglobal Overlapping sequences, primer alignment

Tips

  • For DNA/RNA: Use simple match/mismatch scoring (match=2, mismatch=-1)
  • For proteins: Always use a substitution matrix like BLOSUM62
  • For finding regions: Use local mode instead of global
  • For many alignments: Set max_alignments to limit memory usage
  • Alignment score depends heavily on gap penalties - adjust if results seem wrong