About this Class

Speakers: Dave Clements, Galaxy Community Manager, Johns Hopkins University, Steven Weaver, Senior Programmer Analyst, Temple University Galaxy is an open web-based platform for data integration and analysis in the life sciences. Galaxy makes sophisticated bioinformatics analysis accessible to bench researchers without requiring them to learn Linux system administration or command line interfaces. Every tool and tool setting is automatically recorded by Galaxy, making analyses reproducible by default. Analyses can also be shared with colleagues and with the public, enabling others to re-use and reproduce analyses pipelines. In the first part of this webinar, we will introduce Galaxy and its supporting ecosystem and community. This will include the many ways Galaxy is available to researchers, and a brief overview of the Galaxy user interface. In the second part, we will walk through an application of Galaxy to SARS CoV-2 research. We developed and published public reproducible Galaxy workflows for processing raw deep sequencing read data and calling intra-host genomic variants, as well as processing GISAID full-genome data in a comparative evolutionary framework (covid19.datamonkey.org). The goal of our analysis is to make use of all readily available sources of information to create a frequently updated list of sites in the SARS-CoV-2 genome that may be subject to positive or negative selection. High ranking sites on the list, especially those that are consistently detected over time or accumulate additional evidence in their favor with more data, could be taken as a set of candidates for functional impact or other downstream analyses. We search for evidence of selection at three different evolutionary levels: intra-host (next generation sequencing (NGS) data), between SARS-CoV-2 isolates (assembled genome data), and among beta-coronavirus isolates that are closely related to SARS-CoV-2 (assembled genome data). In this webinar, we will review the comparative analysis dashboard that can be used to which sites may have a functional impact or could be used for further downstream analysis, as well as how Galaxy can be used to implement the pipeline on researchers' datasets. Participants will learn how Galaxy is available, the basics of using Galaxy for data analysis, and how it can be applied in immunology in an example domain. Join ZoomGov Meeting Meeting ID: 161 756 1452 Passcode: 586729 One tap mobile +16692545252,,1617561452#,,,,,,0#,,586729# US (San Jose) +16468287666,,1617561452#,,,,,,0#,,586729# US (New York) Dial by your location +1 669 254 5252 US (San Jose) +1 646 828 7666 US (New York) Meeting ID: 161 756 1452 Passcode: 586729 Find your local number: https://nih.zoomgov.com/u/ayFfvRtd4 Join by SIP 1617561452@sip.zoomgov.com Join by H.323 161.199.138.10 (US West) 161.199.136.10 (US East) Meeting ID: 161 756 1452 Passcode: 586729