Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning

Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin a...

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Veröffentlicht in:bioRxiv 2019
Hauptverfasser: Atak, Zeynep Kalender, Taskiran, Ibrahim Ihsan, Flerin, Christopher, Mauduit, David, Minnoye, Liesbeth, Hulsemans, Gert, Christiaens, Valerie, Ghanem, Ghanem-Elias, Wouters, Jasper, Aerts, Stein
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Sprache:eng
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Zusammenfassung:Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.