Long-read sequencing (LRS) technologies, namely Oxford Nanopore Technologies (ONT) and Pacific Biosciences, have emerged as promising solutions to overcome the limitations of short-read sequencing (SRS). Nevertheless, the still higher sequencing error rates compared to SRS, need for customized pipelines, rapidly updating software and incipient scalability are proving the adoption of the ONT for standard clinical practice to be challenging. Here we assess the performance of ONT (R9 and R10 chemistries) in comparison to Illumina and MGI across 17 well-characterized reference samples with 11 clinical variants representing 9 different genetic diseases. To enable this, we have implemented a production-ready pipeline including SNV, INDEL, STR, SV and CNV detection together with reporting key summary metrics to ensure high quality of data at production sequencing level. Our results show high accuracy of ONT across SNV (F-score >0.975) and SV, but still several weaknesses across INDEL (F-score<0.80). However, we highlight that ONT accurately detected all four pathogenic INDELs as well as the performance improvement in exons and with the newer R10 chemistry. We further demonstrated the importance of long-reads to detect clinical-impacting variants such as a FMR1 pathogenic expansion, often misclassified by SRS as premutation range. Some issues remain as long-read analysis reported the wrong CNV genotype in one of the medical case samples. Remarkably, our multi-platform analysis and Sanger validation discovered a 1-bp error in the Coriell annotation for a cystic fibrosis causing INDEL in GM07829. Overall, this work highlights the readiness of ONT for clinical applications and large-scale operations.

Fritz Sedlazeck receives research support from PacBio, Illumina, Genetech and Oxford Nanopore. Luis F Paulin received research support from Genetech until September 2023 and travel support from Oxford Nanopore in 2023.

This study did not receive any funding

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