NanoSpring

NanoSpring compresses nanopore sequencing reads in FASTQ format (including uncompressed and gzipped inputs) using a reference-free, assembly-based approach to reduce storage of base sequences.


Key Features:

  • Reference-free compression: Implements a reference-free approach based on approximate assembly techniques for compressing read sequences.
  • Nanopore-specific design: Tailored to the characteristics of nanopore sequencing data, including long reads and real-time processing considerations.
  • FASTQ base-sequence focus: Operates on base sequences within FASTQ files for compression.
  • Input formats: Supports both uncompressed and gzipped FASTQ inputs.
  • Compression performance: Achieves compression rates of 0.35 to 0.65 bits per base.
  • Comparison to general compressors: Provides 3 to 6 times better compression than general-purpose compressors such as gzip.
  • Decompression speed: Outperforms the state-of-the-art tool CoLoRd in decompression speed while maintaining competitive compression ratios and resource usage.
  • Dataset validation: Tested on diverse datasets including bacterial, metagenomic, plant, animal, and human whole-genome sequences.

Scientific Applications:

  • Nanopore data storage and archival: Reduces storage footprint of nanopore FASTQ datasets for long-term archival.
  • Real-time nanopore workflows: Supports workflows that require rapid data retrieval during nanopore sequencing runs.
  • Metagenomic sequencing compression: Applicable to compression of metagenomic read datasets.
  • Whole-genome sequencing data management: Applicable to bacterial, plant, animal, and human whole-genome sequencing read datasets.

Methodology:

NanoSpring uses a reference-free approach based on approximate assembly techniques applied to base sequences in FASTQ files, specifically tailored for long nanopore reads and real-time processing characteristics.

Topics

Details

License:
MIT
Cost:
Free of charge
Tool Type:
library
Programming Languages:
C++, Python, C, JavaScript, Other
Added:
11/5/2021
Last Updated:
11/5/2021

Operations

Publications

Meng Q, Chandak S, Zhu Y, Weissman T. NanoSpring: reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach. Unknown Journal. 2021. doi:10.1101/2021.06.09.447198.

Links