Isoform Switching

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/alternative-splicing/isoform-switchingThe 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: Analyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain loss/gain, signal peptide changes, IDR alterations,…

---
name: bio-isoform-switching
description: Analyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain loss/gain, signal peptide changes, IDR alterations, coding-potential shifts). Tools include IsoformSwitchAnalyzeR v2 (auto-selects satuRn for >5 reps else DEXSeq), the manual DRIMSeq -> DEXSeq/satuRn -> stageR DTU pipeline, and fishpond/swish for inferential-uncertainty-aware DTE. Distinguishes DTU from DGE and DTE; integrates external annotators (CPC2, Pfam, SignalP, IUPred2A or DeepTMHMM). Use when investigating how splicing differences alter protein function or trigger NMD-mediated degradation.
tool_type: r
primary_tool: IsoformSwitchAnalyzeR
---

## Version Compatibility

Reference examples tested with: IsoformSwitchAnalyzeR 2.11+, DRIMSeq 1.34+, DEXSeq 1.52+, satuRn 1.14+, stageR 1.28+, fishpond 2.14+, tximport 1.34+, tximeta 1.24+, Salmon 1.10+

Before using code patterns, verify installed versions match. If versions differ:
- 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.

# Isoform Switching and Differential Transcript Usage

Identify shifts in *which* transcript a gene predominantly uses between conditions, and predict functional consequences. Statistically distinct from DGE and DTE; biologically distinct because the same gene-level expression can hide a complete isoform switch with major protein-level consequences.

## DGE vs DTE vs DTU: Which Question Is Being Asked?

| Question | Statistic | Tool | Example claim |
|----------|-----------|------|----------------|
| **DGE** Does the gene total change? | Sum of transcript counts | DESeq2, edgeR, limma-voom | "Gene X is upregulated 2-fold" |
| **DTE** Does this transcript change in absolute abundance? | Per-transcript count | swish (fishpond), DESeq2 on transcripts, sleuth | "Transcript X-201 is upregulated 2-fold" |
| **DTU** Do proportions of transcripts within the gene shift? | Vector of per-transcript proportions | DRIMSeq, DEXSeq, satuRn (+ stageR) | "Gene X switches from isoform 201 (50% -> 10%) to 202 (50% -> 90%)" |

DTU is statistically harder than DGE because:
1. The null is **compositional** (proportions sum to 1; one transcript up means another down).
2. **Multi-stage testing** is required: gene-level "any DTU" + transcript-level "which transcript" -> stageR formalizes this.
3. **Quantification uncertainty propagates** when transcripts are similar (Salmon EM ambiguity).

DTU and event-level differential splicing answer related but distinct questions: rMATS' `IncLevelDifference` is essentially a 1-D projection of a DTU shift onto a single event coordinate. The pragmatic 2026 default: run both an event-level tool (rMATS or leafcutter) and a DTU pipeline; reconcile.

## Tool Selection for DTU

| Tool | Model | When to use | Fails when |
|------|-------|-------------|------------|
| IsoformSwitchAnalyzeR v2 | Wraps DEXSeq or satuRn + functional consequence annotation | Standard interpretation workflow with NMD/domain output | Manual DTU control needed; very large cohorts (>200) |
| DRIMSeq | Dirichlet-multinomial on transcript counts; gene-level DTU | Pre-filter step before DEXSeq/satuRn | Cannot annotate functional consequences alone |
| DEXSeq | Negative-binomial GLM on exon-bin or transcript counts | Classic DTU; conservative; <=5 replicates per condition | Slow at scale; uses bins not transcripts in default mode |
| satuRn | Quasi-binomial GLM with empirical-Bayes shrinkage | DTU at scale (single-cell, large bulk cohorts) | Newer; less battle-tested than DEXSeq |
| swish (fishpond) | Non-parametric SAMseq across Salmon Gibbs samples | DTE/DGE incorporating quantification uncertainty | Requires Gibbs samples; not strictly DTU |
| stageR | Two-stage testing framework | Required for proper OFDR control on top of DRIMSeq/DEXSeq/satuRn | Standalone — wraps another tool's output |
| sleuth | Bootstrap-based DTE on kallisto | When committed to kallisto pipeline | Less active development; superseded by fishpond+swish |

The IsoformSwitchAnalyzeR v2 default rule is: **satuRn if any condition has >5 replicates; else DEXSeq.** For exactly 5 replicates per condition (boundary), explicitly choose; results may differ.

## Decision Tree by Research Question

| Question | Recommended approach |
|----------|----------------------|
| Functional consequences of switches (domains, NMD, signal peptide) | IsoformSwitchAnalyzeR v2 with full external annotator pipeline |
| Pure statistical DTU (gene-level + transcript-level OFDR) | DRIMSeq (filter) -> DEXSeq -> stageR; or -> satuRn -> stageR for n>5 |
| DTU with proper quantification uncertainty | Salmon `--numGibbsSamples 20` -> tximeta -> swish for DTE; concurrent DTU |
| Single-cell DTU | satuRn (DEXSeq doesn't scale to scRNA-seq) |
| Long-read DTU (PacBio Iso-Seq, ONT) | IsoformSwitchAnalyzeR v2 long-read input mode (no Salmon EM uncertainty) |
| Time-course DTU | DEXSeq with time as factor + interaction; or limma::lmFit on logit-prop matrix |
| Cancer / disease — switch hits -> mechanism | Standard pipeline + cross-reference with eCLIP, ClinVar, COSMIC |
| Therapeutic ASO target identification | Standard pipeline + sashimi visualization + SpliceAI design |

## IsoformSwitchAnalyzeR v2 Workflow

**Goal:** Identify isoform switches with functional consequences in one integrated workflow.

**Approach:** Import Salmon, pre-filter, run statistical test (satuRn auto-selected if any condition has >5 replicates, else DEXSeq), annotate switches with external tools (CPC2, Pfam, SignalP, IUPred2A or DeepTMHMM), then summarize consequences.

```r
library(IsoformSwitchAnalyzeR)

salmonQuant <- importIsoformExpression(
    parentDir = 'salmon_quant/',
    add

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.

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 Isoform Switching

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

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