NanoSpring: reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach

Abstract

Motivation: The amount of data produced by genome sequencing experiments has been growing rapidly over the past several years, making compression important for efficient storage, transfer and analysis of the data. In recent years, nanopore sequencing technologies have seen increasing adoption since they are portable, real-time and provide long reads. However, there has been limited progress on compression of nanopore sequencing reads obtained in FASTQ files. Previous work ENANO focuses mostly on quality score compression and does not achieve significant gains for the compression of read sequences over general-purpose compressors. RENANO achieves significantly better compression for read sequences but is limited to aligned data with a reference available. Results: We present NanoSpring, a reference-free compressor for nanopore sequencing reads, relying on an approximate assembly approach. We evaluate NanoSpring on a variety of datasets including bacterial, metagenomic, plant, animal, and human whole genome data. For recently basecalled high quality nanopore datasets, NanoSpring achieves close to 3x improvement in compression over state-of-the-art reference-free compressors. The computational requirements of NanoSpring are practical, although it uses more time and memory during compression than previous tools to achieve the compression gains. Availability: NanoSpring is available on GitHub at https://github.com/qm2/NanoSpring.

Nanopore quality score resolution can be reduced with little effect on downstream analysis

“…Nanopore sequencing, however, is a much more recent technology and few specific data compressors suitable for nanopore data are available, developed by our group [6,7] and others [8,9]. Moreover, the lossy compression of quality scores for nanopore data has only been explored in [9], where the impact of quality score information loss is assessed for some downstream analyses.…”

Nanopore quality score resolution can be reduced with little effect on downstream analysis

“…Nanopore sequencing, however, is a much more recent technology and few specific data compressors suitable for nanopore data are available, developed by our group ( Dufort y Álvarez et al , 2020 , 2021 ) and others ( Kokot et al , 2022 ; Meng et al , 2021 ). Moreover, the lossy compression of quality scores for nanopore data has only been explored in ( Kokot et al , 2022 ), where the impact of quality score information loss is assessed for some downstream analyses.…”