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
Repository
https://github.com/qm2/NanoSpring