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usage_examples
Practical examples for using SQANTI-browser.
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--output my_hub \
--genome hg38That's it! This creates a track hub in my_hub/ ready to upload.
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--output my_hub \
--genome hg38 \
--tablesAdds interactive HTML reports for exploring your data offline.
See Hosting Guide for detailed upload instructions:
- GitHub (easiest)
- Institutional server
- Cloud storage (AWS S3, Google Cloud)
Quick summary: Upload files β Get public URL to hub.txt β Load in UCSC (My Data β Track Hubs)
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--refGTF reference.gtf \
--star-sj SJ.out.tab \
--CAGE-peak CAGE_peaks.bed \
--polyA-peak polyA_peaks.bed \
--tablesWhat this does:
- Shows your transcripts alongside reference annotation
- Adds short-read junction support
- Validates transcription start sites (CAGE)
- Validates termination sites (polyA)
- Creates interactive HTML tables
When to use: Publication-quality visualization with full validation
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome my_species_v1 \
--twobit genome.2bit \
--output my_hubWhen to use: Working with species not in UCSC (e.g., plants, non-model animals)
Note: --twobit automatically extracts chromosome sizes. See Custom Genomes for details.
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--no-category-tracksWhen to use: >50K transcripts, want faster processing
Trade-off: Only creates main track (all transcripts), skips individual category tracks
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--category-tracks FSM,ISM,NICWhen to use: Want only FSM, ISM, and NIC tracks (not all nine categories)
Valid abbreviations: FSM, ISM, NIC, NNC, antisense, genic_intron, genic_genomic (or genic), intergenic, fusion
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--sort-by FLWhen to use: Want to prioritize viewing highly expressed isoforms
Other sort options: length, FL, diff_to_TSS, diff_to_TTS, dist_to_CAGE_peak, dist_to_polyA_site
See Isoform Ordering for details.
--star-sj path/to/SJ.out.tabWhat it does: Shows which junctions have short-read support from STAR alignment
When to use: You have paired short+long read data
--CAGE-peak path/to/CAGE_peaks.bedWhat it does: Validates transcription start sites (5' ends)
Where to get: See SQANTI3 CAGE documentation
When to use: Assess 5' end accuracy
--polyA-peak path/to/polyA_peaks.bedWhat it does: Validates transcription termination sites (3' ends)
Where to get: See SQANTI3 polyA documentation
When to use: Assess 3' end accuracy
--refGTF path/to/reference.gtfWhat it does: Shows reference annotation alongside your transcripts for comparison
Where to get:
- Same file you used with SQANTI3
- GENCODE (human/mouse)
- Ensembl (all species)
- SQANTI3 example (chr22 test data)
When to use: Almost always! Shows context for novel isoforms
| Command | What It Does | When to Use |
|---|---|---|
--validate-only |
Check inputs, don't create hub | Test before full run |
--dry-run |
Process data, skip bigBed creation | Test logic/filters |
--keep-temp |
Keep temporary files | Debug issues |
Example:
# Quick validation (1 second)
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--validate-only
# Full dry run (processes data but doesn't create bigBeds)
python -m sqanti_browser \
--gtf corrected.gtf \
--classification classification.txt \
--genome hg38 \
--output my_hub \
--dry-runGenerate reports without creating a track hub:
python src/filter_isoforms.py \
--classification classification.txt \
--output-dir reportsWith ORF sequences:
python src/filter_isoforms.py \
--classification classification.txt \
--output-dir reports \
--include-sequencesWhen to use: Share data tables with collaborators who don't need UCSC visualization
Run the example workflow script to see commands and parameters:
python example/example_usage.pyTry SQANTI-browser with the included example:
# Basic example
python -m sqanti_browser \
--gtf example/SQANTI3_QC_output/example_corrected.gtf \
--classification example/SQANTI3_QC_output/example_classification.txt \
--output example_output \
--genome hg38 \
--tables
# With all validation tracks
python -m sqanti_browser \
--gtf example/SQANTI3_QC_output/example_corrected.gtf \
--classification example/SQANTI3_QC_output/example_classification.txt \
--genome hg38 \
--output example_output \
--chrom-sizes example/SQANTI3_QC_output/chrom.sizes \
--star-sj example/SQANTI3_QC_output/exampleSJ.out.tab \
--CAGE-peak example/SQANTI3_QC_output/chr22.human.refTSS_v3.1.hg38.bed \
--polyA-peak example/SQANTI3_QC_output/polyApeaks.atlas.GRCh38.bed \
--tables| Tip | Why |
|---|---|
Always use --tables
|
Interactive reports are super useful |
Add --refGTF
|
Compare with reference annotation |
Use --validate-only first |
Catch errors before full run |
Run hubCheck hub.txt
|
Validate before upload |
Sort by FL
|
See highest expressed isoforms first |
Use --no_highlight
|
Disable highlighted isoforms |
- Quick Reference - One-page cheat sheet
- Command Line Reference - All options explained
- Hosting Guide - Upload your hub
- Non-reference Genomes - Working with .2bit files
- SQANTI-reads Integration - Multi-sample experiments
Wiki index
Home
Quick Reference
FAQ
Glossary
Installation Guide
Usage Examples
Hosting Guide
Command Line Reference
Output Files
Interactive HTML Tables
Filtering in UCSC
Trix Search Syntax
Isoform Ordering
Custom Coloring
Working with non-reference genomes
Sharing sessions
Creating subset sessions
SQANTI-reads Integration
Troubleshooting