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Ultra Low Variant Detection: Du Novo Sequencing
Du Novo Sequencing can achieve sub-1% variant detection, which improves on other Duplex Sequencing analysis tools by removing reliance on a reference sequence, preserving a higher proportion of the input reads, and being available for Galaxy. We demonstrate the application of this approach by validating rare variants in the human mitochondrial genome. Dr. Barbara Arbeithuber (Johannes Kepler University Linz, Center for Medical Research) and Dr. Nick Stoler (Penn State University) will present the method and applications in this webinar.
Structural Variant Detection using ONT Data
Long-read sequencing allows for sensitive and accurate detection of structural variants (SV) which are critical to research in genomic applications such as cancer genomics, genetic disease, and crop domestication and improvement. Dr. Nathan Roach (GalaxyWorks) will demonstrate analysis methods of long read data using the Oxford Nanopore (ONT) tool suite in Galaxy Pro. Mr. Michael Alonge (Johns Hopkins University) will highlight his work analyzing 100 diverse tomato accessions to established the largest comprehensive database of SVs in any crop.