Agent skill · Audited from source

Splicing Quantification

skill · GPTomics/bioSkillsMIT licenceAudited 19 Oct 2026 · source c8c1fc3a2b13

★ 1,226pushed 65 days agoarchived repository
✓SAFEGrade B · 89/100 · 19 Oct 2026 · c8c1fc3
1,226repo stars · whole GPTomics/bioSkills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit c8c1fc3a2b13 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters),…

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Cite this page

ModelsAtlas. “Splicing Quantification (GPTomics/bioSkills)”. Retrieved 19 Oct 2026. https://modelsatlas.com/skills/gptomics/splicing-quantification

Trust audit

Audit 0.4.1 · source read 19 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

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

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

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

Provenance

Who published it, and what the verdict is pinned to

  • PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
  • Source folderGPTomics/bioSkills/alternative-splicing/splicing-quantificationThe 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

What it tells the agent

Full source on GitHub ↗

Its description: Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters),…

---
name: bio-splicing-quantification
description: Quantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free intron clusters), VAST-TOOLS (cross-species with microexon support), Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage), or IRFinder-S (intron retention coverage-aware). Distinguishes the five canonical event classes (SE, A5SS, A3SS, MXE, RI), special classes (microexons, exitrons, AFE/ALE), intron retention subtypes (canonical RI vs detained introns), and applies effective-length normalization. Use when measuring splice-site usage or isoform inclusion ratios from short-read RNA-seq.
tool_type: mixed
primary_tool: rMATS-turbo
---

## Version Compatibility

Reference examples tested with: rMATS-turbo 4.3+, SUPPA2 2.4+, leafcutter 0.2.9+, MAJIQ 3.0+, IRFinder-S 2.0+, kallisto 0.50+, Salmon 1.10+, pandas 2.2+, STAR 2.7.11+

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` to verify parameters
- CLI: `<tool> --version` then `<tool> --help` to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# Splicing Quantification

Quantify alternative splicing events as PSI (percent spliced in) from RNA-seq. PSI = inclusion read evidence / (inclusion + skipping read evidence), normalized for differential mapping opportunity between isoforms. The choice of *quantification unit* (event, intron cluster, LSV, transcript) determines which biological questions can be answered and which failure modes apply.

## Algorithmic Taxonomy

| Family | Unit | Reference tools | Fails when |
|--------|------|-----------------|------------|
| Event-based | Pre-defined SE/A5SS/A3SS/MXE/RI events from annotation | rMATS-turbo, SUPPA2, VAST-TOOLS | Event isn't in annotation; complex multi-junction events split arbitrarily; AFE/ALE confounded with splicing |
| LSV-based | Local Splice Variations at single source/target nodes | MAJIQ V3 | Memory-constrained environments; cohorts smaller than ~3 reps; non-academic users (license) |
| Junction-cluster | Annotation-free intron clusters by shared splice sites | leafcutter, leafcutter2 | Undersampled clusters lose power; topology biologically uninterpretable for novel events |
| Splice-graph | Graph nodes (non-overlapping exonic regions) | Whippet, Shiba | Whippet maintenance status uncertain since ~2022; complex multi-exon graphs |
| Coverage-aware (IR) | Intron body coverage + flanking junctions | IRFinder-S, S-IRFindeR, iREAD | Confounded by overlapping exons, repeats, low mappability regions |
| Isoform-based | Transcript abundance via EM | Salmon/kallisto + tximport | Salmon EM uncertainty propagates; many similar isoforms (TTN, MAPT) become indistinguishable |

The agent's first decision is **which family** the question requires, not which tool. Switching family is the response to a tool failing within a family — switching tool within a family rarely fixes systematic blind spots.

## Event Taxonomy (Beyond Standard SE/A5SS/A3SS/MXE/RI)

| Class | Code | Biology | Detection caveat |
|-------|------|---------|-------------------|
| Skipped exon (cassette) | SE | Default cassette-exon AS | Most common; well-handled by all tools |
| Alternative 5' splice site | A5SS | Alternative donor; intron 5' end varies | Sign convention tool-specific (see below) |
| Alternative 3' splice site | A3SS | Alternative acceptor; intron 3' end varies | Sensitive to BPS cancer mutations (SF3B1) — cryptic 3'ss ~10-30nt upstream |
| Mutually exclusive exons | MXE | Two exons paired, one included | Tool implementations vary; verify which "form 1" is yours |
| Retained intron | RI | Whole intron retained in mature mRNA | Junction-only quant systematically underdetects; needs IRFinder-S |
| **Microexon** | (sub-SE) | 3-27 nt; neural-enriched, SRRM4-regulated | Missed by default aligner anchor lengths (>=20-30 nt); needs VAST-TOOLS, MicroExonator, or long-read |
| **Exitron** | n/a | Intronic region within an annotated CDS exon | Mis-classified as A5SS/A3SS by most tools; use ExitronFinder, ScanExitron |
| **Alternative first exon (AFE)** | AFE | Alternative TSS / promoter use | Promoter-driven, NOT spliceosomal; confirm with FANTOM CAGE before reporting as splicing |
| **Alternative last exon (ALE)** | ALE | Alternative cleavage/polyadenylation | APA-driven, NOT spliceosomal; confirm with 3'-end-seq |
| **Detained intron (DI)** | (RI subtype) | Nuclear-retained on mature mRNA, regulated by Clk kinases | Distinct from cytoplasmic NMD-targeted RI (Boutz 2015 *Genes Dev*); requires fractionation to confirm |
| **Recursive splicing** | (intron subtype) | Long introns >50kb spliced via internal ratchet points | Sibley 2015 *Nature*; only detectable with long-read or nascent RNA-seq |

Tool-agnostic taxonomy reference: Wang 2008 *Nature*; Vaquero-Garcia 2016 *eLife* (LSV); Tapial 2017 *Genome Res* (VastDB).

## Tool Selection Matrix

| Tool | Best for | Input | Strengths | Fails when |
|------|----------|-------|-----------|------------|
| rMATS-turbo | Standard SE/A5SS/A3SS/MXE/RI in annotated organism, n>=3 | BAM + GTF | Fast, well-calibrated at n>=3, novel SS support | Junction read imbalance; novel multi-junction events; underdetects RI and microexons |
| SUPPA2 | Quick PSI from existing TPM, pilot analysis | Salmon/kallisto TPM + GTF | No alignment; fastest | Annotation-bound; high FDR (15-30%) at n<=2 vs n<=2 |
| MAJIQ V3 | Complex events, heterogeneous cohorts (HET) | BAM + GFF3 | Bayesian posterior PSI, complete LSV semantics | High memory (~50+ GB on cohorts); academic license; complex LSV interpretation needs care |
| leafcutter | Novel junction discovery, sQTL, 

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.

Install

Pinned to the audited commit c8c1fc3

Download folder ↗
pip install suppa pandas

Commands as the repository documents them: shown, never run by us. Our verdict covers commit c8c1fc3a2b13 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source c8c1fc3a2b13

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Questions about Splicing Quantification

What does the Splicing Quantification skill do?
a set of SKILLS.md for doing bioinformatics with agents like claude code
Is Splicing Quantification safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Splicing Quantification access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (c8c1fc3a2b13), read on 2026-10-19. The repository is watched, and a new audit runs when it changes — this is the first audit.

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