seqeron-epigenetics

name	seqeron-epigenetics
description	Analyze DNA methylation and chromatin state with Seqeron (MCP tools OR the C# API). Use to find CpG sites / CpG islands (Gardiner-Garden & Frommer) and CpG observed/expected ratio, classify CpG/CHG/CHH methylation contexts, call per-CpG methylation from bisulfite sequencing reads (Bismark-style) or forward-simulate bisulfite conversion, aggregate a weighted methylation profile, find differentially methylated regions (DMRs) between two samples (methylKit tiling windows + Fisher exact), estimate epigenetic age (Horvath DNA-methylation clock), predict chromatin state / annotate histone modifications (ChromHMM-style H3K4me3/H3K4me1/H3K27ac/H3K36me3/H3K27me3/H3K9me3), find accessible (ATAC-seq-like) chromatin regions, and predict imprinted genes from allele-specific methylation. Triggers: "find CpG islands", "CpG O/E ratio", "call methylation from bisulfite", "bisulfite-convert this sequence", "methylation profile", "find DMRs between groups", "hyper/hypomethylated regions", "epigenetic age / DNAm age / methylation clock", "predict chromatin state", "annotate histone marks", "accessible chromatin peaks", "imprinted genes". Input is DNA (methylation β-values / read piles for the calling tools). Server: annotation (all EpigeneticsAnalyzer.*).
allowed-tools	Read, Bash, Grep, Glob

seqeron-epigenetics — methylation, bisulfite, DMRs, chromatin, epigenetic age

Routing + orchestration skill for the epigenetics / DNA-methylation family on the annotation server (13 tools, one backing class: EpigeneticsAnalyzer.*). It picks the right tool for a CpG / methylation / bisulfite / DMR / chromatin / epigenetic-age question and gives a dual-mode recipe (MCP tool name and the equivalent Seqeron.Genomics C# Method ID).

• Rigor is delegated. Tool-only computation, provenance, envelope, cross-check, units, 0-based coords, and the alpha / not-for-clinical caveat are owned by bio-rigor — it applies by default; do not restate.
• Don't know a tool name? Use seqeron-discovery (python3 scripts/skills/find-tool.py <kw> --server annotation) — never guess.
• Point, don't duplicate. Full I/O schemas live in docs/mcp/tools/annotation/*.md; algorithm invariants/formulas in docs/algorithms/Epigenetics/*.md.

Scope boundary — this family vs neighbours

• This skill OWNS the DNA-methylation / chromatin family: CpG sites/islands/O-E, methylation contexts (CpG/CHG/CHH), bisulfite calling + simulation, methylation profiles, DMRs, epigenetic age, chromatin-state / histone-mark annotation, accessible regions, imprinted genes. bio-annotation name-drops this family shallowly — route here.
• Everything else annotation (ORFs/genes/promoters, variant calling & effect, motifs/PWMs, repeats/low-complexity, k-mers, splicing, miRNA, RNA-seq) stays in bio-annotation.
• Heterochromatin blocks / G-bands at chromosome scale → find_heterochromatin_regions (chromosome server) via bio-chromosome — distinct from the per-locus predict_chromatin_state/Heterochromatin label here.
• No nucleosome-positioning and no enhancer-caller tool exists. Enhancer states (Active/Weak/Bivalent enhancer) fall out of predict_chromatin_state; there is no standalone nucleosome/enhancer tool — do not fabricate one.

Decision guide — which tool for which question

Question	Tool ([MCP] / Method ID)
Positions of every CpG dinucleotide	find_cpg_sites / EpigeneticsAnalyzer.FindCpGSites
CpG observed/expected ratio for one sequence	cpg_observed_expected / EpigeneticsAnalyzer.CalculateCpGObservedExpected
CpG islands (GC ≥ minGc and O/E ≥ minCpGRatio, merged)	find_cpg_islands / EpigeneticsAnalyzer.FindCpGIslands
Classify C into CpG / CHG / CHH context (sequence-only)	find_methylation_sites / EpigeneticsAnalyzer.FindMethylationSites
Forward-simulate bisulfite conversion of a strand	simulate_bisulfite_conversion / EpigeneticsAnalyzer.SimulateBisulfiteConversion
Call per-CpG methylation level from bisulfite reads	methylation_from_bisulfite / EpigeneticsAnalyzer.CalculateMethylationFromBisulfite
Aggregate sites → weighted global/CpG/CHG/CHH profile	methylation_profile / EpigeneticsAnalyzer.GenerateMethylationProfile
DMRs between two samples (hyper/hypomethylated)	find_dmrs / EpigeneticsAnalyzer.FindDMRs
Epigenetic (DNAm) age from clock CpGs	epigenetic_age / EpigeneticsAnalyzer.CalculateEpigeneticAge
Chromatin state from six histone marks	predict_chromatin_state / EpigeneticsAnalyzer.PredictChromatinState
Per-interval state from a single histone mark	annotate_histone_modifications / EpigeneticsAnalyzer.AnnotateHistoneModifications
Accessible (ATAC-seq-like) chromatin peaks	find_accessible_regions / EpigeneticsAnalyzer.FindAccessibleRegions
Imprinted genes from allele-specific methylation	predict_imprinted_genes / EpigeneticsAnalyzer.PredictImprintedGenes

Coordinates 0-based; island end is exclusive. Methylation levels & β-values are fractions 0..1; histone/accessibility signals 0..1 (out-of-range signal throws for predict_chromatin_state). Confirm exact I/O per tool doc.

Canonical dual-mode pipelines

(a) CpG islands + independent O/E cross-check

1. [MCP] find_cpg_islands(sequence, minLength?=200, minGc?=0.5, minCpGRatio?=0.6) → islands[] (0-based start, exclusive end, gcContent, cpGRatio).
2. [MCP] for a reported island, re-derive its ratio independently: cpg_observed_expected(sequence=island_substring) → ratio should match cpGRatio.

• [C# API] EpigeneticsAnalyzer.FindCpGIslands(...) → .CalculateCpGObservedExpected(...).

Provenance
1) find_cpg_islands(sequence,minLength=200,minGc=0.5,minCpGRatio=0.6) → islands[]
2) cpg_observed_expected(island_substr) → ratio ≈ island.cpGRatio (independent recompute)
Caveat: alpha — validate before use.

(b) Bisulfite reads → per-CpG methylation → profile

1. [MCP] methylation_from_bisulfite(referenceSequence, bisulfiteReads=[{readSequence,startPosition}]) → sites[] (position, type=CpG, methylationLevel, coverage); uncovered CpGs omitted.
2. [MCP] methylation_profile(sites) → weighted globalMethylation/cpGMethylation/cHGMethylation/cHHMethylation, totalCpGSites, methylatedCpGSites, methylationByPosition.

• Optional round-trip check: simulate_bisulfite_conversion(referenceSequence, methylatedPositions) forward-models the reads you then call — a self-consistency oracle.
• [C# API] EpigeneticsAnalyzer.CalculateMethylationFromBisulfite(...) → .GenerateMethylationProfile(...); .SimulateBisulfiteConversion(...).

Provenance
1) methylation_from_bisulfite(ref,reads) → per-CpG sites (level=meC/(meC+unmeC), coverage=C/T calls)
2) methylation_profile(sites) → weighted per-context levels (Schultz 2012)
Cross-check: simulate_bisulfite_conversion(ref,methylatedPositions) reproduces the read pile.
Caveat: alpha.

(c) DMRs between two samples

1. Build each sample's sites[] (from pipeline (b), or caller-supplied).
2. [MCP] find_dmrs(sample1=control, sample2=treatment, windowSize?=1000, minDifference?=0.25, minCpGCount?=3) → regions[] (meanDifference=mean(s2−s1), Fisher pValue, cpGCount, annotation=Hyper/Hypomethylated).

• [C# API] EpigeneticsAnalyzer.FindDMRs(...). Direction is sample2 − sample1 — pass control first. p is two-sided Fisher on pooled counts, not multiple-testing corrected. (Provenance block → reference/pipelines.md §3.)

(d) Chromatin state from histone marks (+ accessibility)

1. [MCP] predict_chromatin_state(h3k4me3,h3k4me1,h3k27ac,h3k36me3,h3k27me3,h3k9me3) → state (ChromHMM-priority: Bivalent* → Active* → Transcribed → Repressed → Heterochromatin → LowSignal). Signals must be 0..1.
2. [MCP] per-interval single-mark labels: annotate_histone_modifications(modifications=[{start,end,mark,signal}]) → annotations[] with predictedState.
3. [MCP] accessible peaks: find_accessible_regions(accessibilitySignal=[{position,signal}], threshold?=0.5, minWidth?=100, maxGap?=50) → regions[] (accessibilityScore, peakType Strong/Moderate/Weak).

• [C# API] .PredictChromatinState(...) · .AnnotateHistoneModifications(...) · .FindAccessibleRegions(...).

(e) Epigenetic age (Horvath clock)

1. [MCP] epigenetic_age(methylationAtClockCpGs={cpgId→β}, coefficients={cpgId→coef}, intercept?=0.0) → age (years, Horvath inverse calibration, adult.age=20). CpGs missing from either side contribute nothing.

• [C# API] EpigeneticsAnalyzer.CalculateEpigeneticAge(...). You supply the published clock coefficient table (wrapper is clock-agnostic) — the result is only as good as that table. (Provenance block → reference/pipelines.md §6.)

Envelope

No epigenetics unit is a guarded unit in docs/Validation/LIMITATIONS.md (no EpigeneticsAnalyzer.* MinimumMode guard; verified 2026-07). So there is no STOP rule specific to this family — but the algorithms are model/heuristic-based (Gardiner-Garden & Frommer thresholds, ChromHMM present/absent binarization at 0.5, methylKit tiling, Horvath calibration). Report results as model output under the stated parameters/thresholds, not ground truth, and keep the alpha / not-for-clinical caveat from bio-rigor. Rule-out results (empty islands/regions/imprinted) are threshold-dependent — record the parameters used.

End-to-end grounded example

Task. From a reference and a pile of bisulfite reads for two conditions, characterise methylation and find DMRs, cross-checking each layer.

1. find_cpg_sites(referenceSequence) → CpG positions (the set DMR windows are built over). (.FindCpGSites)
2. methylation_from_bisulfite(referenceSequence, controlReads) and again with treatmentReads → two sites[]. (.CalculateMethylationFromBisulfite)
3. methylation_profile(each sites[]) → per-condition weighted CpG methylation (sanity summary). (.GenerateMethylationProfile)
4. find_dmrs(control_sites, treatment_sites, windowSize=1000, minDifference=0.25, minCpGCount=3) → regions[]. (.FindDMRs)
5. Cross-check: each DMR's cpGCount and window bounds must fall within the CpG positions from step 1, and meanDifference sign must agree with the two profile levels from step 3.

Provenance
1) find_cpg_sites(ref) → CpG positions
2) methylation_from_bisulfite(ref, controlReads|treatmentReads) → sites per condition
3) methylation_profile(sites) → weighted per-context methylation (cross-check magnitudes)
4) find_dmrs(control,treatment,windowSize=1000,minDifference=0.25,minCpGCount=3) → Hyper/Hypomethylated regions + Fisher p
5) Cross-check: DMR windows ⊆ step-1 CpGs; meanDifference sign agrees with step-3 profiles
Caveat: alpha; thresholds/params are model choices — Fisher p not multiple-testing corrected. Not for clinical use.

Reference

• This family's tool map (all 13 — curated index; NOT in domain-map.json, so there is NO generated slice): reference/tool-map.md
• Fuller recipes + parameter guidance: reference/pipelines.md
• Algorithm background (invariants/formulas — link, don't copy): CpG_Site_Detection.md · Methylation_Analysis.md · Bisulfite_Sequencing_Analysis.md · Differentially_Methylated_Regions.md · Chromatin_State_Prediction.md · Epigenetic_Age_Estimation.md
• Operating envelope: LIMITATIONS.md (no epigenetics guard).
• Cross-cutting: bio-rigor (rigor guardrail) · seqeron-discovery (tool lookup) · bio-annotation (overlap: it name-drops methylation/epigenetics; all other annotation tools live there).