Skip to content

Latest commit

 

History

History
142 lines (113 loc) · 3.49 KB

usage.md

File metadata and controls

142 lines (113 loc) · 3.49 KB

Usage Guide

Basic Usage

panherit --vcf input.vcf --ref reference.fasta --out output_dir

Parameters

  • --vcf: Input VCF file containing structural variants
  • --ref: Reference genome FASTA file
  • --out: Output directory
  • --threads: Number of parallel processing threads (default: 1)
  • --window-size: k-mer window size (default: 4)

Output Structure

output_dir/
├── temp_alignments/        # MUSCLE alignment temporary files
├── variants.bed           # PLINK binary file
├── variants.bim           # PLINK variant information file
├── variants.fam           # PLINK sample information file
└── pipeline.log          # Runtime log

Example

Run with sample data:

panherit \
    --vcf examples/sample.vcf.gz \
    --ref examples/reference.fa \
    --out results \
    --threads 4

Important Notes

  1. Input File Requirements:

    • VCF file must contain structural variant information
    • VCF file should be bgzipped and indexed
    • Reference genome must match VCF coordinate system

  2. Memory Usage:

    • Memory consumption scales with input data size and window size
    • For large datasets, consider increasing available memory

  3. Temporary Files:

    • Temporary files are generated in the output directory during processing
    • Automatic cleanup after successful completion

Troubleshooting

1. MUSCLE Not Found

Error message:

Command 'muscle5' not found

Solution:

  • Verify MUSCLE installation
  • Ensure muscle5 is in system PATH

2. Memory Error

Error message:

MemoryError: Unable to allocate array

Solution:

  • Reduce number of parallel threads
  • Increase system available memory
  • Consider batch processing for large datasets

3. VCF File Format Error

Error message:

InputError: Failed to open VCF file

Solution:

  • Verify VCF file format
  • Check file compression and indexing
  • Validate VCF file integrity with bcftools

Code Examples

Python API Usage

from pangenome_heritability.config import Config
from pangenome_heritability.variant_processing import process_variants
from pangenome_heritability.alignment import run_alignments
from pangenome_heritability.kmer import process_windows
from pangenome_heritability.genotype import convert_to_plink

# Configure parameters
config = Config(
    vcf_file="input.vcf",
    ref_fasta="reference.fa",
    output_dir="results",
    threads=4,
    window_size=4
)

# Run pipeline
variants = process_variants(config)
alignments = run_alignments(config, variants)
windows = process_windows(config, alignments)
bfiles = convert_to_plink(config, windows)

Performance Optimization Tips

  1. Parallel Processing:

    • Increase thread count (--threads) to improve processing speed
    • Recommended not to exceed CPU core count

  2. Memory Management:

    • Window size affects memory usage, adjust as needed
    • Consider batch processing for large datasets

  3. Disk Space:

    • Ensure sufficient space in output directory
    • Temporary files may require significant space

Citation

If you use this tool in your research, please cite:

[Citation information to be added]

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please read our contributing guidelines before submitting pull requests.

Support

For bug reports and feature requests, please use the GitHub issue tracker.

For questions and discussions:

  • Open an issue on GitHub
  • Contact: [contact information]