Isoform Switching

---
name: bio-isoform-switching
description: Analyzes isoform switching events and functional consequences using IsoformSwitchAnalyzeR. Predicts protein domain changes, NMD sensitivity, ORF alterations, and coding potential shifts between conditions. Use when investigating how splicing changes affect protein function.
tool_type: r
primary_tool: IsoformSwitchAnalyzeR
---

# Isoform Switching Analysis

Identify isoform switches and predict their functional consequences on protein structure and function.

## IsoformSwitchAnalyzeR Workflow

```r
library(IsoformSwitchAnalyzeR)

# Import transcript quantification from Salmon
salmonQuant <- importIsoformExpression(
    parentDir = 'salmon_quant/',
    addIsofomIdAsColumn = TRUE
)

# Create switch analysis object
switchAnalyzeRlist <- importRdata(
    isoformCountMatrix = salmonQuant$counts,
    isoformRepExpression = salmonQuant$abundance,
    designMatrix = data.frame(
        sampleID = colnames(salmonQuant$counts),
        condition = c('control', 'control', 'control', 'treatment', 'treatment', 'treatment')
    ),
    isoformExonAnnoation = 'annotation.gtf',
    isoformNtFasta = 'transcripts.fa'
)

# Filter lowly expressed isoforms
switchAnalyzeRlist <- preFilter(
    switchAnalyzeRlist,
    geneExpressionCutoff = 1,  # Minimum TPM
    isoformExpressionCutoff = 0,
    removeSingleIsoformGenes = TRUE
)

# Test for isoform switches
switchAnalyzeRlist <- isoformSwitchTestDEXSeq(
    switchAnalyzeRlist,
    reduceToSwitchingGenes = TRUE
)
```

## Functional Annotation

```r
# Extract sequences for external analysis
switchAnalyzeRlist <- extractSequence(
    switchAnalyzeRlist,
    pathToOutput = 'sequences/',
    writeToFile = TRUE
)

# Run external tools and import results:
# - CPC2 for coding potential
# - Pfam for protein domains
# - SignalP for signal peptides
# - IUPred2 for intrinsic disorder

# After running external tools, import results
switchAnalyzeRlist <- analyzeCPC2(
    switchAnalyzeRlist,
    pathToCPC2resultFile = 'cpc2_results.txt',
    removeNoncodinORFs = TRUE
)

switchAnalyzeRlist <- analyzePFAM(
    switchAnalyzeRlist,
    pathToPFAMresultFile = 'pfam_results.txt'
)

switchAnalyzeRlist <- analyzeSignalP(
    switchAnalyzeRlist,
    pathToSignalPresultFile = 'signalp_results.txt'
)

switchAnalyzeRlist <- analyzeIUPred2A(
    switchAnalyzeRlist,
    pathToIUPred2AresultFile = 'iupred2_results.txt'
)
```

## Consequence Analysis

```r
# Analyze functional consequences of switches
switchAnalyzeRlist <- analyzeSwitchConsequences(
    switchAnalyzeRlist,
    consequencesToAnalyze = c(
        'intron_retention',
        'coding_potential',
        'ORF_seq_similarity',
        'NMD_status',
        'domains_identified',
        'signal_peptide_identified'
    ),
    dIFcutoff = 0.1,  # Minimum isoform fraction change
    showProgress = TRUE
)

# Extract significant switches
significantSwitches <- extractSwitchSummary(
    switchAnalyzeRlist,
    filterForConsequences = TRUE
)

print(significantSwitches)
```

## Visualization

```r
# Plot individual gene switches
switchPlot(
    switchAnalyzeRlist,
    gene = 'GENE_OF_INTEREST',
    condition1 = 'control',
    condition2 = 'treatment'
)

# Summary of consequence types
extractConsequenceSummary(
    switchAnalyzeRlist,
    consequencesToAnalyze = 'all',
    plotGenes = FALSE
)

# Enrichment of consequences
extractConsequenceEnrichment(
    switchAnalyzeRlist,
    consequencesToAnalyze = 'all'
)
```

## Significance Thresholds

| Parameter | Default | Description |
|-----------|---------|-------------|
| Switch q-value | < 0.05 | Significance of isoform switch |
| dIF (delta isoform fraction) | > 0.1 | Minimum usage change |
| Consequence q-value | < 0.05 | Significance of consequence |

## Consequence Types

| Consequence | Impact |
|-------------|--------|
| NMD sensitive | Transcript targeted for degradation |
| Domain loss/gain | Altered protein function |
| ORF disruption | Truncated/altered protein |
| Signal peptide loss | Changed localization |
| Coding potential loss | Switch to non-coding |

## Related Skills

- differential-splicing - Identify differential events first
- splicing-quantification - PSI-level analysis
- pathway-analysis/go-enrichment - Pathway enrichment of switching genes