OLIVER: A Platform for Visualization and Mining of High-Resolution and High-Throughput Data


Executive Summary


Modern genetic tools now allow for rapid, relatively inexpensive sequencing of genetic material from nearly any organism resulting in a data-rich scientific community. Although genomes hold useful information, genetic information alone fails to answer many important biological questions. A major focus in biology now is identifying genetic sources that contribute to complex phenotypes, such as environmental responses and disease. It is known that many traits are not the result of a single gene, but rather small to moderate contributions from several genes resulting in a highly complex relationship between genetic background and resulting phenotype. Genome availability has provided scientists the material to start making complex connections between genetic variation and phenotypes, however, software to aid in the analysis of such large and complex datasets remains lacking.


Description of Technology


Michigan State University has developed advanced data visualization software referred to as OLIVER (Observe, Link, Integrate, Verify, Explore, Reveal). OLIVER is an interactive tool enabling researchers to visualize and interpret complex large-scale data sets. The program displays data primarily in the form of highly interactive heat maps that represent properties (e.g. phenotypic measurements) as a function of another parameter (e.g. genotype). The software was originally designed with the purpose of relating multiple phenotypic measurements collected under dynamic environmental conditions with a large number of genetic variants, however, this software is fundamentally a data analysis tool which could be useful for a number of diverse applications, such as business intelligence or stock market analysis.


Key Benefits

  • Real-time analysis: real time previews of changes to the data allows users to quickly optimize heat maps to display or emphasize information of interest
  • Easy implementation: software can be run on most computers
  • Versatile: useful for any analysis that requires integration of information from several datasets



  • Life Sciences Research
  • Plant Breeding
  • Meteorology
  • Business Intelligence
  • Stock Market Analysis


Patent Status


Under review


Licensing Rights Available


Full licensing rights available


Inventors: David Kramer, Jin Chen, Oliver Tessmer


Tech ID: TEC2015-0045


Patent Information:

For Information, Contact:

Brian Copple
Technology Manager
Michigan State University