| name | bio-alignment |
| description | Align biological sequences and quantify how similar they are with Seqeron (MCP tools OR the C# API). Use for pairwise alignment (global/Needleman-Wunsch, local/Smith-Waterman, semi-global/fitting/overlap), multiple sequence alignment (MSA) + consensus/conservation, percent identity / similarity / gap %, edit (Levenshtein) and Hamming distance, k-mer similarity, longest common region, approximate matching, and prompts like "align these sequences", "how similar are X and Y", "find the conserved region", "does this query fit in that reference". Servers: alignment + core. |
| allowed-tools | Read, Bash, Grep, Glob |
bio-alignment — pairwise/MSA alignment, identity/similarity, distances
Routing + orchestration skill for the Alignment and Core servers (34 tools).
It picks the right tool for an alignment/similarity question and gives a dual-mode
recipe (MCP tool calls and the equivalent Seqeron.Genomics C# Method IDs).
- Rigor is delegated. Parse-with-a-tool, envelope, provenance, cross-check, units/0-based
coordinates, and the alpha / not-for-clinical-use caveat are all owned by
bio-rigor —
it applies here by default; do not restate its rules.
- Don't know the tool name? Use
seqeron-discovery
(python3 scripts/skills/find-tool.py <kw> --server alignment|core) — never guess.
- Point, don't duplicate. Full I/O schemas live in
docs/mcp/tools/{alignment,core}/*.md;
algorithm invariants in docs/algorithms/Alignment/*.md. This skill links, it does not copy.
Decision guide — which tool for which question
| Question | Tool ([MCP] / Method ID) |
|---|
| Align the whole of two seqs end-to-end | global_align / SequenceAligner.GlobalAlign |
| Find the best-scoring shared region (ignore flanks) | local_align / SequenceAligner.LocalAlign |
| Fit a short query into a long reference / overlap / containment | semi_global_align / SequenceAligner.SemiGlobalAlign |
| Identity % / similarity % / gap % of an alignment | alignment_statistics / SequenceAligner.CalculateStatistics |
Pretty-print an alignment (| : legend) | format_alignment / SequenceAligner.FormatAlignment |
| Align N sequences → MSA + consensus | multiple_align / SequenceAligner.MultipleAlign |
| Consensus from pre-aligned equal-length reads | compute_consensus / SequenceAssembler.ComputeConsensus |
| Quick % identity of two equal-length seqs (no gaps) | sequence_identity / SequenceAssembler.CalculateIdentity |
| Edit (Levenshtein) distance (any lengths) | edit_distance / ApproximateMatcher.EditDistance |
| Hamming distance (equal length) | hamming_distance / ApproximateMatcher.HammingDistance |
| k-mer Jaccard similarity (0–1) | calculate_similarity / GenomicAnalyzer.CalculateSimilarity |
| Longest common substring / region (+ positions) | find_longest_common_region / GenomicAnalyzer.FindLongestCommonRegion; text-only: suffix_tree_lcs / SuffixTree.LongestCommonSubstring |
| Approximate match of a pattern (mismatches / edits) | find_with_mismatches, find_with_edits, find_best_match |
Rule of thumb: global for two homologous full-length seqs; local to locate a motif/domain
inside dissimilar seqs; semi-global for overlap/containment (reads → reference, primer-in-amplicon);
MSA for a family; distances/similarity for quick pairwise scoring without a full alignment.
Canonical dual-mode pipelines
Scoring knobs are shared by all pairwise/MSA tools: match (+1), mismatch (−1), gapOpen (−2),
gapExtend (−1 per position, linear gap). Change them together, and report them in provenance.
(a) Global-align two DNA seqs → identity/similarity/gap %
- [MCP]
global_align(sequence1, sequence2) → alignedSequence1, alignedSequence2, score
- [MCP]
alignment_statistics(alignedSequence1, alignedSequence2) → identity, similarity, gapPercent
- [MCP]
format_alignment(…) → human-readable block (optional).
- [C# API]
SequenceAligner.GlobalAlign(s1,s2,match,mismatch,gapOpen,gapExtend) → SequenceAligner.CalculateStatistics(aln1,aln2) → SequenceAligner.FormatAlignment(aln1,aln2,lineWidth).
- Note:
alignment_statistics uses the EMBOSS-needle denominator = full alignment length incl. gap columns; sequence_identity uses a gapless equal-length denominator — pick deliberately.
Provenance
1) global_align(s1,s2,match=1,mismatch=-1,gapOpen=-2,gapExtend=-1) → score, aln1, aln2
2) alignment_statistics(aln1,aln2) → identity=…% , similarity=…% , gapPercent=…% (denominator=aln length incl. gaps)
Cross-check: identity consistent with matches/alignmentLength from the same call.
Envelope: none guarded. Caveat: alpha — validate before any decision use.
(b) Local-align to locate a conserved region
- [MCP]
local_align(sequence1, sequence2) → aligned substrings + startPosition1/2, endPosition1/2 (0-based).
- [MCP]
alignment_statistics(aligned pair) → identity % of the shared core.
- [C# API]
SequenceAligner.LocalAlign(...) → SequenceAligner.CalculateStatistics(...).
- Cross-check the located region with
find_longest_common_region / GenomicAnalyzer.FindLongestCommonRegion (independent suffix-tree path) — positions should agree.
(c) Semi-global for overlap / containment / read-fitting
- [MCP]
semi_global_align(sequence1=query, sequence2=reference) → query gets free end gaps; reference reproduced in full; startPosition2/endPosition2 = where the query lands (0-based).
- [C# API]
SequenceAligner.SemiGlobalAlign(query, reference, …).
- Use for: does read A overlap read B? does a primer/insert fit inside an amplicon? (See pipeline e for exact primer location.)
(d) MSA of N sequences → consensus / conservation
- [MCP]
multiple_align(sequences=[…]) → alignedSequences, consensus, totalScore (sum-of-pairs).
- [MCP] (optional, independent consensus check)
compute_consensus(alignedReads=alignedSequences) → majority-vote consensus (ties → N).
- [C# API]
SequenceAligner.MultipleAlign(seqs,…) → SequenceAssembler.ComputeConsensus(alignedSequences).
- Cross-check:
multiple_align consensus vs compute_consensus on its own rows should match (different code paths).
(e) Quick similarity / distance without a full alignment
- k-mer similarity (0–1):
calculate_similarity(s1,s2,kmerSize?) / GenomicAnalyzer.CalculateSimilarity.
- Edit distance (any length):
edit_distance / ApproximateMatcher.EditDistance.
- Hamming (equal length):
hamming_distance / ApproximateMatcher.HammingDistance.
- Longest common substring:
find_longest_common_region (DNA, with positions) or suffix_tree_lcs (raw text).
- Approximate motif search:
find_with_mismatches (Hamming), find_with_edits (Levenshtein), find_best_match (single best window).
End-to-end grounded example (extends docs/mcp/README.md)
Task. A cloning insert >seq1 GCGCGAATTCATGGATCCATAT is thought to be a variant of a reference
amplicon >ref GCGCGAATTCATGGATCCTTAT. (1) Confirm the insert fits/aligns to the reference, (2) report
identity/similarity/gap %, (3) render the alignment, (4) corroborate the shared core independently.
Tool / Method ID chain (MCP names; C# path in parentheses):
global_align(sequence1="GCGCGAATTCATGGATCCATAT", sequence2="GCGCGAATTCATGGATCCTTAT")
→ score, alignedSequence1, alignedSequence2 (expect a mismatch near the 3′ end, no gaps).
(SequenceAligner.GlobalAlign)alignment_statistics(alignedSequence1, alignedSequence2)
→ identity ≈ 90.9 %, gapPercent = 0 (denominator = 22 aligned columns). (SequenceAligner.CalculateStatistics)format_alignment(alignedSequence1, alignedSequence2, lineWidth=80) → three-line |…| … block. (SequenceAligner.FormatAlignment)- Cross-check:
find_longest_common_region(seq1, ref) → common region GCGCGAATTCATGGATCC at positions
(0,0), length 18 — consistent with the aligned identical prefix. (GenomicAnalyzer.FindLongestCommonRegion)
Expected-shape output (values illustrative; compute them with the tools, do not eyeball):
| id | length | identity_% | similarity_% | gap_% | best_score |
|------|-------:|-----------:|-------------:|------:|-----------:|
| seq1 | 22 | 90.9 | 90.9 | 0.0 | 18 |
Provenance
1) global_align(s1,s2,match=1,mismatch=-1,gapOpen=-2,gapExtend=-1) → score, aln1, aln2
2) alignment_statistics(aln1,aln2) → identity, similarity, gapPercent (denom = alignment length incl. gaps, 0-based cols)
3) format_alignment(aln1,aln2,lineWidth=80) → rendered block
Cross-check: find_longest_common_region(s1,ref) → common core positions agree with the aligned identical prefix.
Envelope: none guarded (Alignment + Core tools within contract).
Caveat: alpha software; not for clinical use — independently validate before relying on any construct decision.
Reference
