Somatic Signatures

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/clinical-databases/somatic-signaturesThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Extracts and assigns COSMIC v3.4 mutational signatures (86 SBS / 11 DBS / 18 ID / 21 CN / 16 SV) from somatic VCFs using SigProfilerSuite, MutationalPatterns, MuSiCal mvNMF, SigNet, or HRDetect. Use when characterizing…

---
name: bio-clinical-databases-somatic-signatures
description: Extracts and assigns COSMIC v3.4 mutational signatures (86 SBS / 11 DBS / 18 ID / 21 CN / 16 SV) from somatic VCFs using SigProfilerSuite, MutationalPatterns, MuSiCal mvNMF, SigNet, or HRDetect. Use when characterizing DNA-damage etiology (BRCA1/2 HRD, MMR-D, POLE, APOBEC3A, UV, tobacco, aflatoxin, 5-FU/SBS17b, platinum, colibactin SBS88), routing PARP inhibitor decisions, or auditing de novo extraction vs refit choice for cohort size.
tool_type: mixed
primary_tool: SigProfilerAssignment
---

## Version Compatibility

Reference examples tested with: SigProfilerMatrixGenerator 1.2+ (Bergstrom 2019), SigProfilerExtractor 1.1.24+ (Islam 2022), SigProfilerAssignment 0.1+ (Diaz-Gay 2023), MutationalPatterns 3.12+ (Manders 2022), MuSiCal 0.7+ (Jin 2024), SigNet (Serrano 2023, bioRxiv), HRDetect (Davies 2017 / Degasperi 2022 implementations), pandas 2.2+, R 4.3+. COSMIC v3.4 (2023, COSMIC v98): 86 SBS, 11 DBS, 18 ID, 21 CN, 16 SV signatures (v3.6 is the current catalog as of 2026).

Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures
- R: `packageVersion('<pkg>')` then `?function_name`

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. COSMIC signature naming evolves: SBS40 was split to SBS40a/b/c in v3.4 (Senkin 2024); SBS17 split to SBS17a/b (5-FU); SBS10 split to SBS10a-d (POLE/POLD1).

# Somatic Mutational Signatures; Etiology, Extraction, Clinical Use

**'Extract mutational signatures from this tumor cohort and identify HRD/MMR/APOBEC processes'** -> Generate 96-context (or DBS/ID/CN/SV) matrix from VCF; choose de novo extraction (NMF) vs refit-to-COSMIC by cohort size; map dominant signatures to etiology; flag clinical actionability.

- Python (recommended): SigProfilerMatrixGenerator -> SigProfilerExtractor (de novo) or SigProfilerAssignment (refit)
- R alternative: `MutationalPatterns::fit_to_signatures()` (strict refit) or `extract_signatures()` (NMF de novo)
- Python (mvNMF for non-uniqueness): MuSiCal (Jin 2024 *Nat Genet*)
- Python (deep learning low-mutation count): SigNet (Serrano 2023)
- R (HRD-specific): HRDetect (Davies 2017 *Nat Med*); the 6-feature BRCA-deficiency classifier

## COSMIC v3.4 Catalog: Evolution and Composition

| Class | Count | Encoding |
|-------|-------|----------|
| **SBS** (Single Base Substitutions) | 86 | 96 trinucleotide contexts (6 substitution types x 16 trinucleotides) |
| **DBS** (Doublet Base Substitutions) | 11 | 78 strand-agnostic doublet classes (Bergstrom 2019) |
| **ID** (Insertion/Deletion) | 18 | 83 categories (indel length x repeat context x microhomology) |
| **CN** (Copy Number) | 21 | 48 channels (total CN x heterozygosity x segment length; Steele 2022 *Nature*) |
| **SV** (Structural Variants) | 16 | 32 channels (cluster x length x type) |

**Recent splits to know:**
- **SBS40 -> SBS40a / SBS40b / SBS40c** (Senkin 2024 *Nature*): pan-cancer active (40a); RCC-specific (40b/c).
- **SBS17 -> SBS17a (T>C uncertain) / SBS17b (T>G in CTT, 5-FU)** (Christensen 2019 *Nat Commun*; Pich 2019 *Nat Genet*).
- **SBS7 -> SBS7a / 7b / 7c / 7d** (UV photoproduct chemistry; Alexandrov 2020).
- **SBS10 -> SBS10a (POLE P286R) / 10b (POLE V411L) / 10c / 10d (POLD1)** (Hodel 2020 *Mol Cell*).

## Etiology Table (Postdoc-grade)

| Signature | Etiology | Clinical implication | Notes |
|-----------|----------|---------------------|-------|
| **SBS1** | Spontaneous 5mC deamination at CpG | Age-correlated; mitotic-rate biomarker | Clock-like |
| **SBS5** | UNKNOWN, clock-like; age-correlated | -- | Reviewer-accepted: "unknown, clock-like"; NOT polymerase fidelity errors |
| **SBS2 / SBS13** | APOBEC (APOBEC3A dominant per Petljak 2022) | Often co-occur; kataegis; ICI response signal | A3A vs A3B via YTCA vs RTCA tetranucleotide ratio |
| **SBS3** | HRD (BRCA1/2 deficient flat profile) | **PARP inhibitor eligibility** | HRDetect 98.7% sensitivity (Davies 2017) |
| **ID6** | HRD microhomology-mediated deletions | PARP eligibility | Pairs with SBS3 |
| **CN17 (HRD-CN1)** | HRD chromosomal instability | PARP eligibility; also BRCA1 promoter hypermethylation | Steele 2022 |
| **SBS6 / 14 / 15 / 20 / 21 / 26 / 44 + ID1 / 2** | MMR-D | ICI eligibility | Lynch typically 6/15/26/44; sporadic MLH1-hyperMet typically 21/26 |
| **SBS14 + SBS20** | POLE+MMR or POLD1+MMR double defect | Ultra-hypermutator; ICI excellent response | >500 mut/Mb |
| **SBS10a / 10b** | POLE-exo P286R / V411L | Hypermutator; ICI excellent response | 100-300 mut/Mb pure POLE |
| **SBS10c / 10d** | POLD1 | -- | Less common |
| **SBS28** | POLE indirect | Often co-extracted with SBS10 | -- |
| **SBS4 + DBS2** | Tobacco smoking; benzo[a]pyrene-G adducts | Lung cancer | C>A bias |
| **SBS7a/b/c/d + DBS1** | UV (CPD vs 6-4 photoproduct chemistry) | Melanoma | CC>TT dipyrimidine, CC>AA |
| **SBS24** | Aflatoxin | HCC (geographic) | C>A at CpC; Schulze 2015 *Nat Genet* |
| **SBS22** | Aristolochic acid | UTC, HCC | T>A at CpTpG; Hoang 2013 *Sci Transl Med* |
| **SBS17b** | 5-Fluorouracil | Therapy-induced | T>G in CTT context |
| **SBS31 / 35 / 86 / 87** | Platinum chemotherapy | Therapy-induced; second cancers | Cisplatin / carboplatin / oxaliplatin |
| **SBS11** | Temozolomide | Glioma post-TMZ | C>T at unmethylated CpC/CpT |
| **SBS88 + ID18** | Colibactin (pks+ E. coli) | CRC etiology; NTHL1-syndrome backgrounds | Pleguezuelos-Manzano 2020 *Nature* |
| **SBS30** | NTHL1 BER deficiency | Lynch-like; cancer predisposition | High cosine to FFPE artifact |
| **SBS-FFPE-artifact** | Formalin-induced C>T (NOT SBS33 as commonly cited) | Sequencing artifact | ~0.90 cosine to SBS30 (formalin-induced C>T characterization in mutational-signatures literature; specific paper attribution removed pending verification) |

**CRITICAL CORREC

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

pip install SigProfilerMatrixGenerator SigProfilerExtractor SigProfilerAssignment
pip install musical

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Somatic Signatures

• github.com/GPTomics/bioSkills/tree/main/clinical-databases/somat — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

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