3-hour genome sequencing and targeted analysis to rapidly assess genetic risk

Galey, Miranda; Reed, Paxton; Wenger, Tara L.; Beckman, Erika; Chang, Irene J.; Paschal, Cate; Buchan, Jillian G.; Lockwood, Christina M.; Puia‐Dumitrescu, Mihai; Garalde, Daniel R.; Guillory, Joseph; Markham, Androo J.; Stergachis, Andrew B.; Bamshad, Michael J.; Eichler, Evan E.; Miller, Danny E.

doi:10.1101/2022.09.09.22279746

Cited by 14 publications

(17 citation statements)

References 31 publications

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“…During large scale nanopore sequencing projects, basecalling is typically performed on external HPC or cloud computer environments, rather than the ONT sequencing device itself 3,5,7,8 . This is relatively slow, computationally expensive and is therefore a barrier to more widespread adoption of nanopore sequencing.…”

Section: Discussionmentioning

confidence: 99%

“…However, in our experience, the PromethION's attached compute tower (PRO-PRCV100) is unable to execute live high-accuracy basecalling on more than ~8-10 flow-cells in parallel. Therefore, to realise even a fraction of the machine's theoretical sequencing throughput, the user must export the raw data and perform basecalling externally on their own high-performance computer (HPC) or cloud environments 3,5,7,8 .…”

Section: Introductionmentioning

confidence: 99%

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Accelerated nanopore basecalling with SLOW5 data format

Samarakoon

Ferguson

Gamaarachchi

2023

Preprint

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Nanopore sequencing is emerging as a key pillar in the genomic technology landscape but computational constraints limiting its scalability remain to be overcome. The translation of raw current signal data into DNA or RNA sequence reads, known as 'basecalling', is a major friction in any nanopore sequencing workflow. Here, we exploit the advantages of the recently developed signal data format 'SLOW5' to streamline and accelerate nanopore basecalling on high-performance computer (HPC) and cloud environments. SLOW5 permits highly efficient sequential data access, eliminating a significant analysis bottleneck. To take advantage of this, we introduce Buttery-eel, an open-source wrapper for Oxford Nanopore's Guppy basecaller that enables SLOW5 data access, resulting in performance improvements that are essential for scalable, affordable basecalling.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Accelerated nanopore basecalling with SLOW5 data format

Samarakoon

Ferguson

Gamaarachchi

2023

Preprint

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“…Longer reads are also necessary to generate high‐quality genome assemblies and phase variants, and to resolve complex SVs at the nucleotide level [114]. Novel informatic platforms also enable faster turnaround times that are important in the intensive care setting [115].…”

Section: What Is Next?mentioning

confidence: 99%

Precision medicine in rare diseases: What is next?

et al. 2023

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Molecular diagnostics is a cornerstone of modern precision medicine, broadly understood as tailoring an individual's treatment, follow‐up, and care based on molecular data. In rare diseases (RDs), molecular diagnoses reveal valuable information about the cause of symptoms, disease progression, familial risk, and in certain cases, unlock access to targeted therapies. Due to decreasing DNA sequencing costs, genome sequencing (GS) is emerging as the primary method for precision diagnostics in RDs. Several ongoing European initiatives for precision medicine have chosen GS as their method of choice. Recent research supports the role for GS as first‐line genetic investigation in individuals with suspected RD, due to its improved diagnostic yield compared to other methods. Moreover, GS can detect a broad range of genetic aberrations including those in noncoding regions, producing comprehensive data that can be periodically reanalyzed for years to come when further evidence emerges. Indeed, targeted drug development and repurposing of medicines can be accelerated as more individuals with RDs receive a molecular diagnosis. Multidisciplinary teams in which clinical specialists collaborate with geneticists, genomics education of professionals and the public, and dialogue with patient advocacy groups are essential elements for the integration of precision medicine into clinical practice worldwide. It is also paramount that large research projects share genetic data and leverage novel technologies to fully diagnose individuals with RDs. In conclusion, GS increases diagnostic yields and is a crucial step toward precision medicine for RDs. Its clinical implementation will enable better patient management, unlock targeted therapies, and guide the development of innovative treatments.

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“…However, variant callers based on deep neural networks (DNN) can produce highly accurate variant calls with long-reads [16,21,22]. Recently, high-throughput long-read sequencing paired with accurate variant calling has demonstrated fastest genetic diagnosis in clinical setting [23,24,25]. Also accurate long-reads shows higher diagnosis rate among individuals who were previously undiagnosed [26,27].…”

Section: Introductionmentioning

confidence: 99%

Local read haplotagging enables accurate long-read small variant calling

Kolesnikov,

Cook,

Nattestad

et al. 2023

Preprint

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Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford nanopore technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation makes DeepVariant a universal variant calling solution for long-read sequencing platforms.

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3-hour genome sequencing and targeted analysis to rapidly assess genetic risk

Cited by 14 publications

References 31 publications

Accelerated nanopore basecalling with SLOW5 data format

Accelerated nanopore basecalling with SLOW5 data format

Precision medicine in rare diseases: What is next?

Local read haplotagging enables accurate long-read small variant calling

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