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A user-friendly software for transcriptome analysis and biomarker discovery


Globally 339 million people are suffering from asthma

It is the most common chronic disease amongst children and each day 1000 people are estimated to die from asthma. Currently, only physiological diagnostic methods are available and several studies show that these methods are unreliable and often leads to misdiagnosis


We strongly believe that biomarkers and biosensor technology could be used to address this problem. This will allow not only for more accurate diagnosis but also an overall better understanding of the genetic components of the disease

We have created ClusteRsy, a user-friendly software for transcriptome analysis and biomarker discovery. Using our software we were able to predict 13 biomarkers for asthma diagnosis and during phase II of the project we will develop a biosensor for this assay



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


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

This year we have developed ClusteRsy, a software for transcriptome data. We predicted 13 biomarkers for asthma and developed a protocol for validation. These biomarkers will be used in a biosensor designed during phase I


During phase II of our project will take the results we acquired so far and validate our predicted biomarkers. This will be done using an antibody based assay such as a sandwich ELISA. Once the biomarkers have been validated we will create antibodies for these and they will finally make it to the biosensor

The validated biomarkers are now ready to be used for our biosensor. Phase II will include in-house antibody production following and optimizing a protocol designed by our collaborator. This is done to reduce the cost of the final product. The lateral flow sensor will use these antibodies as an assay allowing for more accurate diagnosis