Picopore
Picopore compresses and manages large datasets generated by Oxford Nanopore Technologies' MinION and PromethION long-read sequencing platforms to reduce storage requirements while preserving biologically relevant information.
Key Features:
- Lossless compression: Performs lossless compression with an average dataset size reduction of 25% while maintaining complete data fidelity.
- Deep lossless compression: Provides a deep lossless option with an average size reduction of 44% while preserving all original data.
- Raw compression: Offers a raw method that prioritizes retention of biologically relevant information with an average size reduction of 88%.
- Real-time operation: Operates concurrently with sequencing runs to reduce immediate storage demands during MinION and PromethION experiments.
- Redundant file format targeting: Targets highly redundant file formats produced by ONT long-read sequencing to reduce both live-run and archival storage footprints.
Scientific Applications:
- On-run storage reduction: Reduces real-time storage demands on MinION-capable laptops and sequencing systems during data acquisition.
- Archival storage reduction: Lowers long-term archival storage requirements for datasets generated by MinION and PromethION.
- Large-scale dataset management: Enables more storage-efficient handling of large-scale long-read sequencing datasets for genomic research.
Methodology:
Implements three explicitly stated compression methodologies—lossless, deep lossless, and raw—and supports real-time compression concurrent with sequencing runs.
Topics
Collections
Details
- License:
- GPL-3.0
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 8/13/2018
- Last Updated:
- 12/11/2018
Operations
Publications
Gigante S. Picopore: A tool for reducing the storage size of Oxford Nanopore Technologies datasets without loss of functionality. F1000Research. 2017;6:227. doi:10.12688/f1000research.11022.1. PMID:28413619. PMCID:PMC5365225.
Funding: - Australian NHMRC Program: 1054618