SARS-CoV-2
Tutorials covering analysis of SARS-CoV-2 (COVID 19)
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Material
You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides (slides) and tutorial (tutorial) buttons below.Assembly
Lesson | Slides | Hands-on | Recordings | Input dataset | Workflows |
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Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads |
Computational chemistry
Lesson | Slides | Hands-on | Recordings | Input dataset | Workflows |
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Virtual screening of the SARS-CoV-2 main protease with rxDock and pose scoring |
Using Galaxy and Managing your Data
Lesson | Slides | Hands-on | Recordings | Input dataset | Workflows |
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Automating Galaxy workflows using the command line | |||||
SRA Aligned Read Format to Speed Up SARS-CoV-2 data Analysis | |||||
Submitting sequence data to ENA |
Sequence analysis
Lesson | Slides | Hands-on | Recordings | Input dataset | Workflows |
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Removal of human reads from SARS-CoV-2 sequencing data | |||||
SARS-CoV-2 Viral Sample Alignment and Variant Visualization |
Variant Analysis
Lesson | Slides | Hands-on | Recordings | Input dataset | Workflows |
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From NCBI's Sequence Read Archive (SRA) to Galaxy: SARS-CoV-2 variant analysis | |||||
Mutation calling, viral genome reconstruction and lineage/clade assignment from SARS-CoV-2 sequencing data |
Editorial Board
This material is reviewed by our Editorial Board:
Wolfgang MaierContributors
This material was contributed to by:
Dave Clements Natalie Kucher Simon Bray Miguel Roncoroni Wolfgang Maier Jon Trow Elizabeth Humphries Boris Depoortere Anton Nekrutenko Candace Savonen Bert Droesbeke Katherine Cox Bérénice Batut Daniel Blankenberg Adelaide Rhodes Marius van den Beek Robert Meller Ava Hoffman Frederick TanFunding
These individuals or organisations provided funding support for the development of this resource
NHGRI GDS Community Network
NHGRI ANVIL
ELIXIR-CONVERGE
ELIXIR CONVERGE is connecting and align ELIXIR Nodes to deliver sustainable FAIR life-science data management services. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement № 871075
BeYond-COVID
BY-COVID is an EC funded project that tackles the data challenges that can hinder effective pandemic response.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement № 101046203 (BY-COVID)