Publication Date
Summer 6-30-2014
Description
Next generation sequencing (NGS) systems produce vast quantities of data that require substantial computational resources for typical analysis tasks. In addition, data that are generated by different NGS systems are not homogeneous. Moreover, there are an overwhelming number of tools available for performing typical tasks. Managing NGS workflows involves writing custom scripts that quickly grow in complexity, often resulting in unwieldy workflows that underutilize typical high performance compute resources, and increase the demands of the staff managing these workflows. We present Node-Oriented Workflow (NOW), a dynamic command template workflow engine for high performance distributed computing (HPC) systems. Our system provides a simple-to-use browser-based front end for designing and managing complex workflows. Workflows are configured using a simple browser interface, and are managed by the integrated job engine, which initializes nodes, monitors node status, and processes results of individual jobs across nodes in an HPC configuration. We reduce excessive messaging across nodes by placing the burden on nodes to start tasks in a workflow when dependencies are met, i.e., node oriented workflow. Our system was designed for NGS processing in the clinical research setting, emphasizing user simplicity, tool scalability, minimization of redundancy in workflows, while maximizing throughput in an HPC environment. Furthermore, NOW is not restricted to NGS pipeline management, but can used to manage any computational pipeline.
Journal
Journal of Data Mining in Genomics & Proteomics
Volume
5
Issue
2
Department
Computer Science
Link to Published Version
http://omicsonline.org/open-access/nodeoriented-workflow-now-a-command-template-workflow-management-tool-for-high-throughput-data-analysis-pipelines-2153-0602-5-159.php?aid=31903
Recommended Citation
Lipsky, Eric B.; King, Brian R.; and Tromp, Gerard. "Node-Oriented Workflow (NOW): A Command Template Workflow Management Tool for High Throughput Data Analysis Pipelines." Journal of Data Mining in Genomics & Proteomics (2014) .