Dannon Baker, Marius Van Den Beek, Dave Bouvier, John Chilton, Nate Coraor, Simon Gladman, Björn Grüning, Delphine Larivière, Andrew Lonie, Nicholas Keener, Sergei Kosakovsky Pond, Wolfgang Maier, Anton Nekrutenko, James Taylor, Steven Weaver

This repo serves as a companion to our study describing the analysis of early COVID-19 data. It contains descriptions of workflows and exact versions of all software used. The goals of this study were to:

1. Underscore the importance of access to raw data
2. Demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid reproducible research during global crises

Our analysis was divided into six parts listed below. Each part has a dedicated page that provides links to input datasets, intermediate and final results, workflows, and Galaxy histories that list all details for each analysis. These workflows can be re-run by anyone on two global Galaxy instances in the US and in Europe.

1. Pre-processing of raw read data
2. Assembly of COVID-19 genome
3. Estimation of timing for most recent common ancestor (MRCA)
4. Analysis of variation within individual isolates
5. Analysis of Spike protein substitutions
6. Analysis of recombination and selection

The analyses have been performed using the Galaxy platform and open source tools from BioConda. Tool runs used XSEDE resources maintained by the Texas Advanced Computing Center (TACC), Pittsburgh Supercomputing Center (PSC), and Indiana University in the U.S., de.NBI cloud resources on the European side, and ARDC cloud resources in Australia.