ScanExitron

A computational workflow for exitron splicing identification from RNA-Seq data.

---

🌟 Features

• Accurate Identification: High-performance detection of exitrons (exonic introns) directly from aligned RNA-Seq reads (BAM/CRAM).
• VCF Conversion: Built-in support to convert results into standard VCF files for downstream variant analysis.
• Bioconda Support: Easy deployment along with all underlying command-line dependencies.

---

🚀 Installation

Option 1: Via Bioconda (Recommended)

This installs scanexitron along with all required external compiled tools automatically:

conda install -c bioconda scanexitron

Option 2: Via PyPI

Installs the Python package. Note: You must install the external dependencies separately (see below).

pip install scanexitron

Option 3: From Source

git clone https://github.com/ylab-hi/ScanExitron.git
cd ScanExitron
pip install -e ".[dev]"

---

🛠️ External Dependencies

If you did not install via conda, make sure the following bioinformatics tools are installed and available on your system PATH:

Dependency	Required Version	Conda Install Command
🛠️ regtools	0.5.0	conda install -c bioconda regtools=0.5.0
🧬 samtools	≥ 1.10	conda install -c bioconda samtools
🗃️ bedtools	≥ 2.26	conda install -c bioconda bedtools

---

📂 Reference Data Setup

Download your genome FASTA and matching transcript annotation files. For example, to setup hg38 reference resources:

# Download and decompress the hg38 genome
wget https://hgdownload.cse.ucsc.edu/goldenpath/hg38/bigZips/hg38.fa.gz
gunzip hg38.fa.gz

# Download and decompress the Gencode release annotation
wget ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_37/gencode.v37.annotation.gtf.gz
gunzip gencode.v37.annotation.gtf.gz

---

💻 Usage

🔍 1. Exitron Calling

Run scanexitron by pointing it to your reference FASTA, transcript annotation GTF, and the input BAM/CRAM file (which must have a .bai/.crai index file alongside it):

scanexitron -r hg38.fa -g gencode.v37.annotation.gtf input.bam

Calling Options

Flag	Default	Description
INPUT	Required	Path to the input BAM/CRAM file.
-r, --ref	Required	Path to the reference genome FASTA file.
-g, --gtf	Required	Path to the annotation GTF file.
-a, --ao	3	Minimum junction-spanning reads supporting the exitron.
-p, --pso	0.05	Minimum Percent Spliced Out (PSO) value.
-m, --mapq	50	Minimum mapping quality for alignment filtering.
-s, --strand	1	Strand specificity: 0 = unstranded, 1 = first-strand/RF, 2 = second-strand/FR.
-t, --threads	1	Number of threads to allocate for samtools.
-o, --output	Input Stem	Output prefix.
--verbose	Off	Enable verbose logging for debugging.

---

🔄 2. Convert to VCF

Format your exitron tabular output into a standard VCF file using exitron2vcf:

exitron2vcf -r hg38.fa -o sample.vcf sample.exitron

VCF Converter Options

Flag	Default	Description
INPUT	Required	Path to the input tabular results (.exitron file).
-r, --ref	Required	Path to the reference genome FASTA file.
-o, --output	output.vcf	Path for the output VCF file.

---

📊 Output Format

Results are written to <input>.exitron as a tab-delimited file with the following schema:

Column	Type	Description
chrom	String	Chromosome name
start	Integer	Start position (0-based, half-open)
end	Integer	End position (0-based, half-open)
name	String	Junction identifier
ao	Integer	Number of supporting junction reads
strand	String	Genomic strand (+ or -)
gene_symbol	String	HGNC gene symbol
length	Integer	Exitron length in base pairs
splice_site	String	Donor–acceptor dinucleotides (e.g., GT-AG)
gene_id	String	Ensembl gene ID
pso	Float	Percent Spliced Out (relative exitron abundance)
psi	Float	Percent Spliced In
dp	Float	Average local sequencing depth
total_junctions	Integer	Total junction-spanning reads detected in the sample

Note: RegTools intermediate files (<input>.janno) are preserved in the directory for manual inspection.

---

👩‍💻 Development

Contributions and local development setups are welcome:

# Install development and testing dependencies
pip install -e ".[dev]"

# Run test suite
pytest

---

📖 Citation

If you use ScanExitron in your research, please cite our papers:

• Molecular Cell: Molecular Cell Publication
• STAR Protocols: STAR Protocols Publication

---

📄 License

This project is licensed under the terms of the MIT License.

---

📬 Contact & Support

• Bug Reports & Feature Requests: Please submit an issue on the GitHub Issues tracker.