Journal article an interactive catalogue of analysis methods for long-read sequencing data

Shanika L Amarasinghe, Matthew E Ritchie, Quentin Gouil



BACKGROUND: The data produced by long-read third-generation sequencers have unique characteristics compared to short-read sequencing data, often requiring tailored analysis tools for tasks ranging from quality control to downstream processing. The rapid growth in software that addresses these challenges for different genomics applications is difficult to keep track of, which makes it hard for users to choose the most appropriate tool for their analysis goal and for developers to identify areas of need and existing solutions to benchmark against. FINDINGS: We describe the implementation of, an open-source database that organizes the rapidly expanding collection of long-rea..

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University of Melbourne Researchers


Awarded by Silicon Valley Community Foundation

Awarded by Australian National Health and Medical Research Council (NHMRC)

Funding Acknowledgements

This work was supported by funding from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation (grant No. 2019-002443 to MER), a fellowship from the Australian National Health and Medical Research Council (NHMRC, grant No. GNT1104924 to MER), Victorian State Government Operational Infrastructure Support, and Australian Government NHMRC IRIISS.