Dorado

Advancements in Secondary Analysis for Variant Calling

Thydian Windsor, a Research Scientist in the Machine Learning team at Oxford Nanopore Technologies, gave the secondary analysis update at the Nanopore Community Meeting. They defined secondary analysis as “what does the collection of reads say in aggregate?” For variant calling, improvements on the base-calling side with base-calling models and motor enzymes have been released. […]
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Oxford Nanopore’s Dorado: Key Features and Enhancements Explained

Mike Vella, Senior Director of Machine Learning for Oxford Nanopore Technologies, provided an update on Dorado at the Nanopore Community Meeting in Boston. Vella explained that Dorado “powers Nanopore base-calling” by converting the raw signals into sequences. Stand-alone Dorado is a command-line tool. Dorado is also integrated into MinKNOW. Vella announced that among the updates, […]
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ATCC Insights: Base-Calling in Genomics

David Yarmosh from ATCC presented at the Nanopore Community Meeting in Boston. The session’s title was intriguing: “How good is good enough?” Yarmosh is a bioinformatician with ATCC. They noted that the ATCC was founded in 1925 and now has nearly 5,000 genomes. Yarmosh explained that they are doing about 1,000 genome assemblies per year. […]
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Basecaller Advancements 2024: New Models and Speed Improvements

Basecaller updates are more frequent now, with new models and speed improvements. Tonight, I watched the London Calling 2024 session on basecaller advancements. Sam Davis, Principal Scientist, Machine Learning with Oxford Nanopore Technologies (ONT), spoke about the recently released models and chemistries. The V5 models offer 1.5Q accuracy improvement when compared to previous versions. Davis […]
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Maximize Nanopore Basecalling with Dorado: Latest Updates and Features

I want to learn how to fully utilize Dorado base calling features. Tonight, I watched Susie Lee, Technical Product Manager for Basecalling and Models at Oxford Nanopore Technologies, present the latest updates to Dorado at London Calling 2024. They explained Dorado as a software tool that “powers Nanopore basecalling and more” by taking raw signal […]
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Genomic Surveillance of Multi-Drug Resistant Organisms with Long-Read Sequencing

Today was the first day of our IPERT Summer Workshops! I also started watching London Calling 2024 videos available on the YouTube channel. I began with the session titled “Genomic surveillance of multidrug-resistant organisms based on long-read sequencing.” Fabian Landman works at the Centre for Infectious Disease Control in The Netherlands and the Dutch National […]
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2023 Dorado Updates

Joyjit Daw, a Principal Machine Learning Engineer at Oxford Nanopore Technologies (ONT), provided a Dorado update at the Nanopore Community Meeting Houston meeting. The Dorado v0.5.0 release supports core Guppy features, custom barcodes, read splitting, and Minimap2 alignment. Dorado has been integrated into MinKNOW. They have also extended features such as hemi methylation for the […]
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Cell-free DNA for Methylation-based Diagnostics

Billy Lau from Stanford University School of Medicine spoke at the Nanopore Community Meeting in Houston about “Nanopore sequencing of cell-free DNA for methylation-based breast cancer detection.” I have watched Lau speak at other ONT events. This session was about a research study to improve cancer detection. Lau spoke about breast cancer detection issues. Liquid […]
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Midyear Nanopore Update

Rosemary Sinclair Dokos, the SVP of Product and Programme Management at Oxford Nanopore Technologies, presented an updated at the Nanopore Community Meeting in Singapore 2023. They considered this a mid-year update since their major updates were during London Calling 2023. Oxford Nanopore Technologies (ONT) strives for “Towards the Sequencing of Anything by Anyone Anywhere.” Sinclair […]
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The New Dorado Basecaller is Available!

Mark Bricknell, a Realtime Analysis Fellow with Oxford Nanopore Technologies, spoke at London Calling 2023. The title of the session is “Dorado – the future of basecalling.” I have been thinking about basecalling and duplex reads today. Bricknell explained that basecalling uses recurrent neural networks that are computationally intensive to interpret raw signals into sequences. […]
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