AnVIL Magic 2020

Massive Genome Informatics in the Cloud (MaGIC) Jamboree

Virtual Jamboree
Jun 10, 2020 and Jun 11, 2020
11:00 AM ET


Jamboree agenda with slide links


An introduction to the AnVIL platform to enable CCDG and CMG researchers to analyze GSP data using AnVIL tools. Participants will gain exposure and familiarity with available data, tools, workflows, training materials, and support channels of AnVIL. Participants will not become bioinformatic experts, but will know what to do or who to contact when the time comes.


In summer 2020, NHGRI plans to organize Massive Genome Informatics in the Cloud or MaGIC, a two-day, jamboree-style informatics event for introducing new users to the AnVIL platform for cloud-based genomics data analysis.


No computational expertise is required. Anyone from GSP who would like to learn about cloud based genomic analysis on AnVIL. This Jamboree will focus on highlighting interactive tools that are used from a graphical user interface.

Virtual Event Agenda, all Times ET

Day 1 (June 10th, 2020)

11:00 AMNHGRI welcome and introduction (lecture)
11:05 AMAnVIL introduction (lecture)
11:30 AMTerra - data access and discovery (lecture)
12:00 PMAnVIL data catalog and exploration (lecture)
12:30 PMBreak
1:30 PMLinking billing accounts, eRA commons account on Terra (hands-on)
2:00 PMUsing AnVIL to access, browse, and share data (hand-on)
2:30 PMBreakout sessions
3:00 PMClosing

Day 2 (June 11th, 2020)

11:00 AMData analysis on AnVIL - use cases (lecture)
11:15 AMDockstore and WDL (lecture)
11:45 AMTerra - for data analysis (lecture)
12:00 PMConcept of Workspaces (hands-on*)
12:30 PMBreak
1:30 PMBatch processing of data with Workflows (hands-on*)
2:00 PMExploratory analysis with Notebooks & R Studio (hands-on*)
2:25 PMJamboree closing
2:30 PMBreakout sessions

More Info

This will be a virtual event on Zoom that will be recorded. Hands-on sections will be lead by AnVIL presenters, participants are invited to follow along in real time. Hands on sections on day 2 will work through an analysis example analyzing 1000 genomes data.


Please feel free to pass on any questions to Shurjo Sen or Mo Heydarian.

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