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

Abstract

We investigate the effect of quality score information loss on downstream analysis from nanopore sequencing FASTQ files. We polished denovo 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 cause little difference on (or even improves) the results obtained with the original (non-quantized) data. This suggests that the precision that is currently used for nanopore quality scores is 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.

An efficient method to prepare barcoded cDNA libraries from plant callus for long-read sequencing

“…Reads showed an average quality score across all bases over 15 and all above 7 as recommended by Nanopore. This indicates an accuracy higher than 96.8% [21], which is considered as assigning con dence for long reads with little effect on downstream analysis [22,23]. Therefore, barcoded libraries prepared using this protocol are suitable for further analysis.…”