HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis

Authors

Ross A. Smith
Rhonda J. Vickery
Jack Harris
Sara Gharabaghi, Wright State University - Main CampusFollow
Thomas Wischgoll, Wright State University - Main CampusFollow
David Short, Wright State University - Main Campus
Robert Trevino
Steven A. Kawamoto
Thomas J. Lamkin
Kevin Schoen
Eric E. Bardes
Scott C. Tabar
Bruce J. Aronow

Document Type

Conference Proceeding

Publication Date

2016

Abstract

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.

Comments

The International Conference for High Performance Computing, Networking, Storage, and Analysis, November, 13-18, 2016, Salt Lake City, UT.

Repository Citation

Smith, R. A., Vickery, R. J., Harris, J., Gharabaghi, S., Wischgoll, T., Short, D., Trevino, R., Kawamoto, S. A., Lamkin, T. J., Schoen, K., Bardes, E. E., Tabar, S. C., & Aronow, B. J. (2016). HPC Enabled Data Analytics for High-Throughput High-Content Cellular Analysis. .
https://corescholar.libraries.wright.edu/cse/469