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 |
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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. |
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