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

Links

Repository
https://anaconda.org/bioconda/picopore
(Bioconda package)
Repository
https://pypi.org/project/picopore/
(Python Software Foundation)