Pegasus WMS: Enabling Bioinformatics using Workflow Technologies. G. Mehta1, E. Deelman1, K. Vahi1, Y. Wang2,4, A. Clark3, R. Mayani1, T. Chen4, J. Knowles3 1) Information Sciences Institute, University of Southern California, Marina Del Rey, CA; 2) Department of Automation, Xiamen University, China; 3) Department of Psychiatry, USC Keck School of Medicine, Los Angeles, CA; 4) Department of Biological Sciences, University of Southern California, Los Angeles, CA.

   Recent advances in bioinformatics from genome sequencing techniques, to protein analysis to bacterial RNA studies have resulted in large amounts of raw data being generated. This data needs to be analyzed, mapped to genomes as well as handled in a robust, efficient and secure manner. Generally most laboratories lack the tools or the manpower to create complex pipelines to analyze these datasets and run these pipelines on the computing infrastructure present either in the laboratories or on campus or the commercial cloud environments. 
   To enable scientists to run their bioinformatics analyses on large-scale computational resources we use Pegasus WMS, a Workflow Management System that can manage large-scale scientific workflows across local, Grid, and Cloud resources simultaneously. Pegasus WMS provides a means for representing the application as a workflow in an abstract XML form, agnostic of the resources available to run it on and the location of the input data and executables. It then, compiles these workflows into executable workflows by querying catalogs and farming computations across local and distributed computing resources, as well as emerging commercial and community cloud environments in an easy and reliable manner. Pegasus WMS optimizes the execution as well as data movement by leveraging existing Grid and cloud technologies via flexible pluggable interfaces and provides advanced features like data reuse, automatic cleanup of generated data, and hierarchal workflows with deferred compilation. It also captures all the provenance of the workflow from the compilation stage to the execution of the generated data, helping scientists accurately measure performance metrics of their workflow as well as tackle data reproducibility issues. 
   Pegasus WMS has also been packaged in an easy to use Virtual Machine that can be used on local machines or clusters to run RNA Sequencing Workflows using different Genome mapping tools and expression calculators for the NIMH Transcriptional Atlas of Human Brain Development project. It was recently used to compute more then 200 samples of human RNA samples on a campus cluster. Pegasus WMS was initially developed to support large-scale high-energy physics and astrophysics experiments and supports a wide variety of applications from earthquake simulation, bacterial RNA studies, helioseismology to bioinformatics.