intronIC 2.4.3

Intron classification tool for identifying U2-type and U12-type introns using SVM

intronIC (intron Interrogator and Classifier)

Classify intron sequences as U12-type (minor spliceosome) or U2-type (major spliceosome). A 126-model multispecies RBF SVM ensemble scores each intron against position-weight matrices and outputs a calibrated probability (0-100%).

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Quick Start

pip install intronIC

# Classify introns (loads default model automatically)
intronIC -g genome.fa.gz -a annotation.gff3.gz -n species_name -p 8

# Extract sequences without classification
intronIC extract -g genome.fa.gz -a annotation.gff3.gz -n species_name -p 8

# Verify installation with bundled test data
intronIC test -p 4

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What's New in v2.4

• Default model is now the v3 multispecies bundle: 3 seeds × 42 calibrated SVMs (126 total) trained on 41,333 introns across 90 species and 14 clades. Holdout F1 = 1.000 vs the v2.3 default's 0.9975, and ~54% lower production-equivalent FPR on U12-absent species.
• Default classification threshold lowered from 95 → 90, made safe by the v3 model's tighter calibration. Pass --threshold 95 to restore prior behavior.
• --streaming (default) and --in-memory now produce bit-identical classifications. Mode choice affects only the runtime/memory tradeoff. Reference run on Homo sapiens GRCh38 + Ensembl 104, -p 6, ~227k scored introns: streaming ~16 min / 5.4 GB peak, in-memory ~15 min / 10.1 GB peak.
• Self-describing model bundles carry config + training metadata alongside the weights; see docs/v3_bundle_schema.md.
• v2.3 model bundles continue to load unchanged; old runs reproduce by passing --model <v2.3-bundle.pkl>.
• See CHANGELOG.md for full release history.

What's New in v2.3

• 42-model RBF SVM ensemble on a streamlined 6D feature set
• Bayesian score adjustment suppresses false positives in species lacking a distinct U12-type intron population, using a species-level valley prior and per-intron ensemble agreement
• Species-specific U2-type background correction for cross-species composition bias
• Default threshold raised to 95% for higher-confidence calls (now lowered to 90 in v2.4)

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Key Features

• Probability scores (0-100%) from a 126-model calibrated SVM ensemble (3 seeds × 42 sub-models, isotonic calibration)
• Pretrained model loaded automatically for cross-species analysis
• Streaming mode (default) roughly halves peak memory on large genomes (e.g., ~5.4 GB vs ~10.1 GB for full human at -p 6); bit-identical classifications
• Parallel scoring via -p N for linear speedup
• Comprehensive metadata: phase, position, parent gene/transcript

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How It Works

Most eukaryotic introns (~99.5%) are spliced by the major (U2-type) spliceosome; a small fraction (~0.5%) are spliced by the minor (U12-type) spliceosome. U12-type introns carry a conserved TCCTTAAC branch point motif and have either AT-AC (~25%) or GT-AG (~75%) terminal dinucleotides.

intronIC identifies U12-type introns in five stages:

1. PWM scoring — score the 5' splice site, branch point, and 3' splice site against position-weight matrices
2. Background correction — blend species-specific nucleotide frequencies into U2-type PWMs to correct composition bias
3. Normalization — convert raw log-odds to z-scores via robust scaling
4. SVM classification — 126-model RBF SVM ensemble (v2.4 default; 3 seeds × 42 sub-models) produces per-intron probabilities and ensemble agreement (sigma)
5. Score adjustment — adjust probabilities using a species-level valley prior and an ensemble disagreement penalty

See Technical Details for the full algorithm description.

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Documentation

Full documentation lives in the intronIC Wiki:

• Quick Start — Installation, dependencies, resource usage
• Overview — Classification approach and scientific background
• Output Files — File formats and score interpretation
• Technical Details — Algorithm, features, score adjustment
• Usage Info — Complete CLI reference
• Example Usage — Common workflows
• Changelog — Release notes and version history

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Citation

If you use intronIC in your research, please cite:

Moyer DC, Larue GE, Hershberger CE, Roy SW, Padgett RA. (2020) Comprehensive database and evolutionary dynamics of U12-type introns. Nucleic Acids Research 48(13):7066-7078. doi:10.1093/nar/gkaa464

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Support

• intronIC Wiki — Documentation
• GitHub Issues — Bug reports
• GitHub Discussions — Questions and ideas

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Contributing

See CONTRIBUTING.md for guidelines.

git clone https://github.com/glarue/intronIC.git
cd intronIC
make install    # Set up development environment
make test       # Run tests

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License

GNU General Public License v3.0