Case Study: University of Manchester reveals human growth patterns with Qlucore Omics Explorer

University of Manchester analyzes 400+ microarrays with Qlucore

The University of Manchester's research group, led by Dr. Adam Stevens, faced the challenge of analyzing large transcriptomic datasets to understand human growth patterns. Their technical situation involved integrating complex omics data from blood samples, and a fundamental problem was the difficulty in finding statisticians who also understood the specific biology of their research on childhood growth and growth hormone treatments.

The solution was implemented using Qlucore Omics Explorer. Its visually-driven and intuitive interface allowed the biologists to perform powerful statistical analysis themselves without needing advanced expertise. Qlucore enabled the group to efficiently handle large datasets of 400 microarrays and use visualization to explore hypothesis-free data, interpret findings, and clearly explain their methodology to non-expert reviewers.

University of Manchester