bio-phylo-popgen

name	bio-phylo-popgen
description	Build phylogenetic trees and compute population-genetics statistics with Seqeron (MCP tools OR the C# API). Phylogenetics: distance matrices (p-distance / Jukes-Cantor / Kimura-2P / Hamming), tree construction (Neighbor-Joining, UPGMA), Newick parse/serialize, tree stats (depth, length, leaves, MRCA, patristic + Robinson-Foulds distance), bootstrap support. Population genetics: allele/genotype frequencies, minor allele frequency (MAF) + MAF filtering, Hardy-Weinberg equilibrium test, Fst / F-statistics / pairwise Fst, nucleotide diversity (π), Watterson's θ, Tajima's D, heterozygosity, linkage disequilibrium (D'/r²) + haplotype blocks, runs of homozygosity / inbreeding, iHS, ancestry, selection scans. Triggers: "build a tree", "make a phylogeny / dendrogram from these sequences", "neighbor-joining / UPGMA tree", "distance matrix", "compute Fst", "test Hardy-Weinberg / HWE", "nucleotide diversity of this population", "Tajima's D", "linkage disequilibrium", "MAF filter". Servers: phylogenetics + population.
allowed-tools	Read, Bash, Grep, Glob

bio-phylo-popgen — phylogeny + population genetics

Routing + orchestration skill for the Phylogenetics (13) and Population (18) servers = 31 tools. It picks the right tool for a tree-building or popgen 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 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 phylogenetics|population) — never guess.
• Point, don't duplicate. Full I/O schemas live in docs/mcp/tools/{phylogenetics,population}/*.md; algorithm invariants in docs/algorithms/{Phylogenetics,Population_Genetics}/*.md. This skill links, it does not copy.

Decision guide — which tool for which question

Question	Tool ([MCP] / Method ID)
Build a tree from aligned sequences (distance + NJ/UPGMA in one step)	build_phylogenetic_tree / PhylogeneticAnalyzer.BuildTree
Build a tree from a precomputed distance matrix	build_tree_from_matrix / PhylogeneticAnalyzer.BuildTreeFromMatrix
Pairwise distance matrix of aligned seqs	distance_matrix / PhylogeneticAnalyzer.CalculateDistanceMatrix
Evolutionary distance between two aligned seqs	pairwise_distance / PhylogeneticAnalyzer.CalculatePairwiseDistance
Serialize / parse Newick	to_newick / .ToNewick · parse_newick / .ParseNewick
Tree stats (height / total length / leaves)	tree_depth .GetTreeDepth · tree_length .CalculateTreeLength · tree_leaves .GetLeaves
MRCA / path length between taxa	mrca .FindMRCA · patristic_distance .PatristicDistance
Compare two trees (topology distance)	robinson_foulds_distance / .RobinsonFouldsDistance
Clade support (resampling)	bootstrap_support / .Bootstrap
Allele frequencies from genotype counts	allele_frequencies / PopulationGeneticsAnalyzer.CalculateAlleleFrequencies
MAF from a genotype vector · filter variants by MAF	minor_allele_frequency .CalculateMAF · filter_variants_by_maf .FilterByMAF
Hardy-Weinberg equilibrium test	hardy_weinberg_test / .TestHardyWeinberg
Fst (two pops) · F-statistics (Fis/Fit/Fst) · pairwise Fst matrix	fst .CalculateFst · f_statistics .CalculateFStatistics · pairwise_fst .CalculatePairwiseFst
Nucleotide diversity π · Watterson's θ · all diversity stats in one pass	nucleotide_diversity .CalculateNucleotideDiversity · wattersons_theta .CalculateWattersonTheta · diversity_statistics .CalculateDiversityStatistics
Tajima's D (neutrality)	tajimas_d / .CalculateTajimasD
Linkage disequilibrium (D'/r²) · haplotype blocks	linkage_disequilibrium .CalculateLD · haplotype_blocks .FindHaplotypeBlocks
Runs of homozygosity · inbreeding F_ROH	runs_of_homozygosity .FindROH · inbreeding_from_roh .CalculateInbreedingFromROH
iHS · ancestry · selection scan	integrated_haplotype_score .CalculateIHS · estimate_ancestry .EstimateAncestry · scan_selection_signals .ScanForSelection

Rule of thumb: UPGMA → rooted, ultrametric (assumes a molecular clock); Neighbor-Joining → unrooted, no clock assumption (prefer for real divergence data). Distance model: Hamming/PDistance for closely related seqs; JukesCantor/Kimura2Parameter correct for multiple hits but return +Infinity at saturation (p ≥ 0.75). Default distance model is JukesCantor, default tree method is UPGMA.

Canonical dual-mode pipelines

Method IDs on the PopulationGeneticsAnalyzer / PhylogeneticAnalyzer classes. Full param/return schemas are in the linked per-tool docs — do not guess parameters.

(a) Aligned sequences → distance matrix → NJ/UPGMA tree → Newick + stats

1. [MCP] build_phylogenetic_tree(sequences={name→alignedSeq}, distanceMethod=JukesCantor, treeMethod=NeighborJoining) → newick, taxa, distanceMatrix, method.
2. [MCP] tree_length(newick) + tree_depth(newick) + tree_leaves(newick) → tree summary.

• [C# API] PhylogeneticAnalyzer.BuildTree(sequences, distanceMethod, treeMethod) → .CalculateTreeLength / .GetTreeDepth / .GetLeaves.
• Cross-check: run distance_matrix(alignedSequences, method) independently and confirm it equals the distanceMatrix echoed by build_phylogenetic_tree; or feed that matrix to build_tree_from_matrix and compare the Newick.

Provenance
1) build_phylogenetic_tree(distanceMethod=JukesCantor, treeMethod=NeighborJoining) → newick, distanceMatrix
2) tree_length/tree_depth/tree_leaves(newick) → stats
Cross-check: distance_matrix(same method) == echoed distanceMatrix.
Envelope: none guarded. Caveat: alpha — validate before any decision use.

(b) Genotype counts → allele/genotype frequencies → Hardy-Weinberg test

1. [MCP] allele_frequencies(homozygousMajor, heterozygous, homozygousMinor) → majorFreq p, minorFreq q.
2. [MCP] hardy_weinberg_test(variantId, observedAA, observedAa, observedaa, significanceLevel=0.05) → expectedAA/Aa/aa, chiSquare, pValue, inEquilibrium.

• [C# API] .CalculateAlleleFrequencies(nAA,nAa,naa) → .TestHardyWeinberg(id,AA,Aa,aa,alpha).
• Cross-check: HWE-expected 2pqn should use the same p from step 1; inEquilibrium ⇔ pValue ≥ α (1 df χ²).

(c) Two populations' allele frequencies → Fst / F-statistics

1. [MCP] fst(population1=[{alleleFreq,sampleSize}…], population2=[…]) → fst (Wright, in [0,1]).
2. [MCP] (optional) f_statistics(…) → Fis, Fit, Fst; for >2 pops use pairwise_fst → symmetric matrix.

• [C# API] .CalculateFst(pop1,pop2) · .CalculateFStatistics(...) · .CalculatePairwiseFst(...).
• Per-locus counts must match between the two populations (error 1001 otherwise). Fst=0 panmixia, 1 fixed difference.

(d) Aligned population sample → nucleotide diversity / Tajima's D (neutrality)

1. [MCP] diversity_statistics(sequences=[aligned…]) → nucleotideDiversity π, wattersonTheta, tajimasD, segregatingSites S, sampleSize n, observed/expected heterozygosity — one pass.

• [C# API] .CalculateDiversityStatistics(sequences).
• Cross-check / split path: nucleotide_diversity (π only) and wattersons_theta(S,n,L); then tajimas_d(averagePairwiseDifferences=k̂=π·L, segregatingSites=S, sampleSize=n) — Tajima's D takes k̂ (NOT per-site). D<0 excess rare variants (expansion/purifying); D>0 deficit (balancing/contraction).

(e) Genotype data → MAF filtering / linkage disequilibrium

1. [MCP] minor_allele_frequency(genotypes=[0/1/2…]) → maf ∈ [0,0.5]; filter_variants_by_maf(variants, minMAF=0.01, maxMAF=0.5) → variants passing (filters on stored alleleFrequency, does NOT recompute).
2. [MCP] linkage_disequilibrium(variant1Id, variant2Id, genotypes=[{geno1,geno2}…], distance) → dPrime, rSquared; chain into haplotype_blocks for block structure.

• [C# API] .CalculateMAF(genotypes) · .FilterByMAF(variants,min,max) · .CalculateLD(...) · .FindHaplotypeBlocks(...).

End-to-end grounded example (extends docs/mcp/README.md)

Task. Four aligned orthologs A,B,C,D (equal length). (1) Build an NJ tree, (2) report total tree length + leaf branch lengths, (3) test whether the sample departs from neutrality, (4) corroborate the distances independently.

Tool / Method ID chain (MCP names; C# path in parentheses):

1. build_phylogenetic_tree(sequences={A,B,C,D}, distanceMethod="JukesCantor", treeMethod="NeighborJoining") → newick, distanceMatrix, taxa. (PhylogeneticAnalyzer.BuildTree)
2. tree_length(newick) → total branch length; tree_leaves(newick) → per-taxon branch lengths. (.CalculateTreeLength, .GetLeaves)
3. diversity_statistics(sequences=[A,B,C,D]) → π, wattersonTheta, tajimasD, S, n. (.CalculateDiversityStatistics)
4. Cross-check: distance_matrix(alignedSequences, method="JukesCantor") must equal the distanceMatrix echoed in step 1. (.CalculateDistanceMatrix)

Expected-shape output (values illustrative; compute them with the tools, do not eyeball):

| tree_method | leaves | tree_length | pi     | wattersonTheta | tajimasD | S |
|-------------|-------:|------------:|-------:|---------------:|---------:|--:|
| NJ          |      4 |        …    |   …    |       …        |    …     | … |

Provenance
1) build_phylogenetic_tree(distanceMethod=JukesCantor, treeMethod=NeighborJoining) → newick, distanceMatrix
2) tree_length(newick), tree_leaves(newick) → branch lengths
3) diversity_statistics([A,B,C,D]) → pi, wattersonTheta, tajimasD, S, n
Cross-check: distance_matrix(JukesCantor) == echoed distanceMatrix.
Envelope: none guarded (Phylogenetics + Population tools within contract).
Caveat: alpha software; not for clinical use — independently validate before relying on any result.

Reference

• Full domain tool index (all 31, generated — do NOT hand-edit): _generated/tools.md (produced by scripts/skills/gen-catalog.py; if absent, run seqeron-discovery).
• Fuller recipes + parameter/model guidance: reference/pipelines.md
• Tool map (all 31 by sub-task, one-liners + Method ID): reference/tool-map.md
• Algorithm background (invariants/formulas — link, don't copy): docs/algorithms/Phylogenetics/Tree_Construction.md · Distance_Matrix.md · Newick_Format.md · Tree_Statistics.md · Tree_Comparison.md · Bootstrap_Analysis.md · Population_Genetics/Diversity_Statistics.md · F_Statistics.md · Hardy_Weinberg_Test.md · Allele_Frequency.md · Linkage_Disequilibrium.md
• Cross-cutting: bio-rigor (rigor guardrail) · seqeron-discovery (tool lookup).