Impact of lossy compression of nanopore raw signal data on basecall and consensus accuracy

Motivation Nanopore sequencing provides a real-time and portable solution to genomic sequencing, with long reads enabling better assembly and structural variant discovery than second generation technologies. The nanopore sequencing process generates huge amounts of data in the form of raw current data, which must be compressed to enable efficient storage and transfer. Since the raw current data is inherently noisy, lossy compression has potential to significantly reduce space requirements without adversely impacting performance of downstream applications.

Results We study the impact of two state-of-the-art lossy time-series compressors applied to nanopore raw current data, evaluating the tradeoff between compressed size and basecalling/consensus accuracy. We test several basecallers and consensus tools on a variety of datasets at varying depths of coverage, and conclude that lossy compression can provide as much as 40-50% reduction in compressed size of raw signal data with negligible impact on basecalling and consensus accuracy.