339 MILLIONS PEOPLE SUFFERING FROM ASTHMA WORLDWIDE
ClusteRsy
ClusteRsy software designed for analyzing transcriptome data to determine gene expression in any RNA-sequencing data set. A primary aim of the software is to be user-friendly and intuitive to use. With a designed workflow allowing the user to seamlessly analyze, visualize and interpret their data leading to a further understanding of any disease. The results retrieved can also be a key factor when searching for potential biomarkers
Modelling
Through our computational pipeline using ClusteRsy we were able to predict 13 biomarkers for asthma diagnosis. We could show that using a modular approach with our model increases the chance of getting significant results and the model is powerful enough to discover heterogeneity within a disease. This led to a discovery that surprised us, a connection between RSV bronchiolitis and asthma was found and our results could be used to screen infants with a high risk for a severe form of RSV
Theoretical Biosensor
The primary goal of the project is to acquire molecular information of asthma and to create more refined methods for asthma diagnosis. RNA-sequencing data of patients with allergic asthma have been used as a pilot and has shown very promising results of potential biomarkers. Once the biomarkers have been validated they will be used as an assay in a lateral flow sensor