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Prioritization of Exome Data by Image Analysis

The aim of the PEDIA study is to investigate the value of computer-assisted analysis of medical images and clinical features in the diagnostic workup of patients with rare genetic disorders. For this purpose, the phenotypic similarities of a patient to all known monogenic disorders (OMIM) are first quantified using next-generation phenotyping (NGP) approaches. The resulting similarity scores are then combined with deleteriousness scores from the molecular level to prioritize potential disease genes. 

The performance of the approach is evaluated by assessing the diagnnostic yield that can be accomplished by working through this list. For the current cohort, the disease-causing gene is listed at the first position in more than 9 out of ten cases (top-1-accuracy rate of 91%). If you are interested in becoming a colaborator of the study or using the software for diagnostics, please have a loog at for further details and contact us!

Participants of Translate NAMSE can now join PEDIA:



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If you are a patient and are interested in participating, please contact your closest ZSE.



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