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

Abstract

Motivation The use of high precision for representing quality scores in nanopore sequencing data makes these scores hard to compress and, thus, responsible for most of the information stored in losslessly compressed FASTQ files. This motivates the investigation of the effect of quality score information loss on downstream analysis from nanopore sequencing FASTQ files. Results We polished de novo assemblies for a mock microbial community and a human genome, and we called variants on a human genome. We repeated these experiments using various pipelines, under various coverage level scenarios, and various quality score quantizers. In all cases we found that the quantization of quality scores causes little difference (or even sometimes improves) on the results obtained with the original (non-quantized) data. This suggests that the precision that is currently used for nanopore quality scores may be unnecessarily high, and motivates the use of lossy compression algorithms for this kind of data. Moreover, we show that even a non-specialized compressor, like gzip, yields large storage space savings after quantization of quality scores. Availability Quantizers freely available for download at: https://github.com/mrivarauy/QS-Quantizer Supplementary information Available at https://github.com/mrivarauy/QS-Quantizer

Reference-free lossless compression of nanopore sequencing reads using an approximate assembly approach

“…Note that while quality scores occupy a significant amount of space even after compression, we focus on read sequences due to the relative lack of research in this area, and since quality scores are often ignored by downstream tools like minimap2 7 . Quality scores have also been compressed lossily without an impact on the downstream performance for short-read technologies 8 , 9 and more recently for nanopore itself 10 , 11 . RENANO 12 is a recent reference-based compressor that achieves significantly better compression for read sequences, but is limited to aligned data with a reference available.…”