isoform-switching

Name: isoform-switching
Author: GPTomics

1.1kstars185forks

How to install isoform-switching?

gptomics/bioskills/isoform-switching

$npx -y skills add GPTomics/bioSkills --skill isoform-switching

Installs into the current project.

Summary

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-s

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SKILL.md

1	## Version Compatibility
2
3	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+
4
5	Before using code patterns, verify installed versions match. If versions differ:
6	- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
7	- CLI: `<tool> --version` then `<tool> --help` to confirm flags
8
9	If code throws ImportError, AttributeError, or TypeError, introspect the installed
10	package and adapt the example to match the actual API rather than retrying.
11
12	# Isoform Switching and Differential Transcript Usage
13
14	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.
15
16	## DGE vs DTE vs DTU: Which Question Is Being Asked?
17
18	\| Question \| Statistic \| Tool \| Example claim \|
19	\|----------\|-----------\|------\|----------------\|
20	\| DGE Does the gene total change? \| Sum of transcript counts \| DESeq2, edgeR, limma-voom \| "Gene X is upregulated 2-fold" \|
21	\| DTE Does this transcript change in absolute abundance? \| Per-transcript count \| swish (fishpond), DESeq2 on transcripts, sleuth \| "Transcript X-201 is upregulated 2-fold" \|
22	\| 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%)" \|
23
24	DTU is statistically harder than DGE because:
25	1. The null is compositional (proportions sum to 1; one transcript up means another down).
26	2. Multi-stage testing is required: gene-level "any DTU" + transcript-level "which transcript" -> stageR formalizes this.
27	3. Quantification uncertainty propagates when transcripts are similar (Salmon EM ambiguity).
28
29	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.
30
31	## Tool Selection for DTU
32
33	\| Tool \| Model \| When to use \| Fails when \|
34	\|------\|-------\|-------------\|------------\|
35	\| IsoformSwitchAnalyzeR v2 \| Wraps DEXSeq or satuRn + functional consequence annotation \| Standard interpretation workflow with NMD/domain output \| Manual DTU control needed; very large cohorts (>200) \|
36	\| DRIMSeq \| Dirichlet-multinomial on transcript counts; gene-level DTU \| Pre-filter step before DEXSeq/satuRn \| Cannot annotate functional consequences alone \|
37	\| 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 \|
38	\| satuRn \| Quasi-binomial GLM with empirical-Bayes shrinkage \| DTU at scale (single-cell, large bulk cohorts) \| Newer; less battle-tested than DEXSeq \|
39	\| swish (fishpond) \| Non-parametric SAMseq across Salmon Gibbs samples \| DTE/DGE incorporating quantification uncertainty \| Requires Gibbs samples; not strictly DTU \|
40	\| stageR \| Two-stage testing framework \| Required for proper OFDR control on top of DRIMSeq/DEXSeq/satuRn \| Standalone — wraps another tool's output \|
41	\| sleuth \| Bootstrap-based DTE on kallisto \| When committed to kallisto pipeline \| Less active development; superseded by fishpond+swish \|
42
43	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.
44
45	## Decision Tree by Research Question
46
47	\| Question \| Recommended approach \|
48	\|----------\|----------------------\|
49	\| Functional consequences of switches (domains, NMD, signal peptide) \| IsoformSwitchAnalyzeR v2 with full external annotator pipeline \|
50	\| Pure statistical DTU (gene-level + transcript-level OFDR) \| DRIMSeq (filter) -> DEXSeq -> stageR; or -> satuRn -> stageR for n>5 \|
51	\| DTU with proper quantification uncertainty \| Salmon `--numGibbsSamples 20` -> tximeta -> swish for DTE; concurrent DTU

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isoform-switching

1.1kstars185forks

View on GitHub

How to install isoform-switching?

gptomics/bioskills/isoform-switching

$npx -y skills add GPTomics/bioSkills --skill isoform-switching

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	## Version Compatibility
2
3	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+
4
5	Before using code patterns, verify installed versions match. If versions differ:
6	- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
7	- CLI: `<tool> --version` then `<tool> --help` to confirm flags
8
9	If code throws ImportError, AttributeError, or TypeError, introspect the installed
10	package and adapt the example to match the actual API rather than retrying.
11
12	# Isoform Switching and Differential Transcript Usage
13
14	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.
15
16	## DGE vs DTE vs DTU: Which Question Is Being Asked?
17
18	\| Question \| Statistic \| Tool \| Example claim \|
19	\|----------\|-----------\|------\|----------------\|
20	\| DGE Does the gene total change? \| Sum of transcript counts \| DESeq2, edgeR, limma-voom \| "Gene X is upregulated 2-fold" \|
21	\| DTE Does this transcript change in absolute abundance? \| Per-transcript count \| swish (fishpond), DESeq2 on transcripts, sleuth \| "Transcript X-201 is upregulated 2-fold" \|
22	\| 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%)" \|
23
24	DTU is statistically harder than DGE because:
25	1. The null is compositional (proportions sum to 1; one transcript up means another down).
26	2. Multi-stage testing is required: gene-level "any DTU" + transcript-level "which transcript" -> stageR formalizes this.
27	3. Quantification uncertainty propagates when transcripts are similar (Salmon EM ambiguity).
28
29	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.
30
31	## Tool Selection for DTU
32
33	\| Tool \| Model \| When to use \| Fails when \|
34	\|------\|-------\|-------------\|------------\|
35	\| IsoformSwitchAnalyzeR v2 \| Wraps DEXSeq or satuRn + functional consequence annotation \| Standard interpretation workflow with NMD/domain output \| Manual DTU control needed; very large cohorts (>200) \|
36	\| DRIMSeq \| Dirichlet-multinomial on transcript counts; gene-level DTU \| Pre-filter step before DEXSeq/satuRn \| Cannot annotate functional consequences alone \|
37	\| 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 \|
38	\| satuRn \| Quasi-binomial GLM with empirical-Bayes shrinkage \| DTU at scale (single-cell, large bulk cohorts) \| Newer; less battle-tested than DEXSeq \|
39	\| swish (fishpond) \| Non-parametric SAMseq across Salmon Gibbs samples \| DTE/DGE incorporating quantification uncertainty \| Requires Gibbs samples; not strictly DTU \|
40	\| stageR \| Two-stage testing framework \| Required for proper OFDR control on top of DRIMSeq/DEXSeq/satuRn \| Standalone — wraps another tool's output \|
41	\| sleuth \| Bootstrap-based DTE on kallisto \| When committed to kallisto pipeline \| Less active development; superseded by fishpond+swish \|
42
43	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.
44
45	## Decision Tree by Research Question
46
47	\| Question \| Recommended approach \|
48	\|----------\|----------------------\|
49	\| Functional consequences of switches (domains, NMD, signal peptide) \| IsoformSwitchAnalyzeR v2 with full external annotator pipeline \|
50	\| Pure statistical DTU (gene-level + transcript-level OFDR) \| DRIMSeq (filter) -> DEXSeq -> stageR; or -> satuRn -> stageR for n>5 \|
51	\| DTU with proper quantification uncertainty \| Salmon `--numGibbsSamples 20` -> tximeta -> swish for DTE; concurrent DTU

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6 picks

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