Illumina Relaunches Correlation Engine, Banking on Need for ‘Omics Informatics Tools
By Allison Proffitt
May 11, 2023 | Illumina is relaunching its BaseSpace Correlation Engine—now simply Illumina Correlation Engine—as the sequencing company emphasizes connecting its informatics components together, Mike LeliveIt, VP of Product Management, told Bio-IT World. “What people want now is for the components to talk to each other so they can get work done and they don’t have to build tools. Our shift to Illumina Connected Software really represents the importance of what we’re building.”
Editor’s Note: Anushka Brownley, Associate Director, Product Management, Illumina will be speaking on “Omic Data Potential for Biomarker Discovery and Optimize Lab Operations” at a lunch session at the Bio-IT World Conference & Expo on Thursday, May 18, in the Data Science and Analytics Technologies track.
Correlation Engine is a collection of curated knowledge bases that Illumina acquired in 2013 with its acquisition of NextBio. For a decade, the curation team at Illumina has been looking at public datasets and published literature mining for biological interactions. “On top of this collection of knowledge bases, we have analytical tools that are really designed to identify correlations between these biological entities,” Lelivelt explains.
Lelivelt sees Correlation Engine fitting at the end of the Illumina Connected Software pipeline that begins with Clarity LIMS in the lab, includes instrumentation and DRAGEN software, and adds Connected Analytics and Connected Insights.
Correlation Engine takes the outputs of discovery and enables researchers to ask: “What more can I find out about this list of things that I ran in the experiment? What happens to this list in other samples, other tissues? Does it cause similar disease states?... Do you see a pattern in different model organisms?” LeliveIt explains. “It’s that correlation that helps drive genomics discovery.”
While this sort of correlation has always been valuable—and indeed Correlation Engine has been consistently populated with data and used by researchers—Lelivelt argues that we are in an era of increased value thanks to the variety of 'omics data now available.
“Now we’re getting to more precise data. What’s happened across the last decade is at the RNA level we’ve gone from, ‘I can measure the mean level of a whole bunch of cells,’ to ‘I can measure each different cell type expression and identify it.’ The single cell revolutionized the amount of information that was given for a lot of discovery experiments, and now spatial includes cell-to-cell relationships… That’s a whole other level of information.”
Life science’s current data volume makes tools like Correlation Engine ever more valuable, Lelivelt says.
“Without tools to hang all this together—provide algorithms to let things float to the top and let humans see the interactions—it’s difficult to mine it. It’s the continued iteration of how important these algorithmic tools are for our understanding of these complex biological systems we look at.”
