Article Spotlight: Creating a splice variant decision tree

Published on 01/10/2023

2 min read

Discover how Dr. Mohamed Z Alimohamed used Alamut™️ to develop a decision tree for the prioritization of potential RNA splice variants in cardiomyopathy genes.

Dr. Mohamed Z Alimohamed kindly summarized his upcoming peer-reviewed publication in Gene

“Current splice prediction algorithms have limited sensitivity and specificity, therefore many potential splice variants are classified as variants of uncertain significance (VUSs). 

However, functional assessment of VUSs to test splicing is labor-intensive and time-consuming. We have developed a decision tree, SEPT-GD, by setting thresholds for the splice prediction programs implemented in Alamut™️ to prioritize potential splice variants associated with cardiomyopathies for functional studies, and functionally verified the outcome of the decision tree.

SEPT-GD outperforms the tools commonly used for RNA splicing prediction and improves prioritization of variants in cardiomyopathy genes for functional splicing analysis.”

Dr. Alimohamed presenting his award-winning poster of this research at the ASHG (American Society of Human Genetics) Annual Meeting.

Click here to read the full publication.

Alimohamed MZ, Boven LG, van Dijk KK, Vos YJ, Hoedemaekers YM, van der Zwaag PA, Sijmons RH, Jongbloed JDH, Sikkema-Raddatz B, Westers H. SEPT-GD: A decision tree to prioritise potential RNA splice variants in cardiomyopathy genes for functional splicing assays in diagnostics. Gene. 2023 Jan 30;851:146984.

Schematic representation of Splice Effect Prediction Tree – Genome Diagnostics (SEPT–GD).

Alamut™️ is for Research Use Only. Not for use in diagnostic procedures.

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