We would like to invite you to attend the 8th webinar in BioExcel’s
webinar series on computational methods and applications for
biomolecular research, which will take place on 16th November 2016:

Presenter: Ravi Madduri (introduction by Stian Soiland-Reyes)

When: Wed 16th November 2016 16:00 CET (2016-11-16 15:00 UTC)

Registration: Free

In this BioExcel webinar we are delighted to have Ravi Madduri from Argonne National Laboratory and University of Chicago present Globus Genomics, a system developed for rapid analysis of large quantities of next-generation sequencing (NGS) genomic data, combining Galaxy workflows with cloud technologies like Amazon EC2 and Globus File Transfer.

This system achieves a high degree of end-to-end automation that encompasses every stage of data analysis including initial data retrieval from remote sequencing centers or storage (via the Globus file transfer system); specification, configuration, and reuse of multi-step processing pipelines (via the Galaxy workflow system); creation of custom Amazon Machine Images and on-demand resource acquisition via a specialized elastic provisioner (on Amazon EC2); and efficient scheduling of these pipelines over many processors (via the HTCondor scheduler).

The system allows biomedical researchers to perform rapid analysis of large NGS datasets in a fully automated manner, without software installation or a need for any local computing infrastructure.

Ravi’s work is part of the BD2K center Big Data for Discovery Science, building infrastructure for reproducible workflows using minids (minimal viable identifiers), analyzing data at scale using identified Docker containers, publish results in to Globus Publication services thus providing an end-to-end framework for reproducible research.

In this BioExcel webinar, Ravi will present Globus Genomics and the technologies used to achieve large-scale analytical Galaxy workflows on the cloud. We think this will be of interest not just for the genomics community, but for any scientific workflow users who need to consider distributed deployments, data management and scalability.