RT Journal Article
SR Electronic
T1 Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2019.12.21.885806
DO 10.1101/2019.12.21.885806
A1 Zeynep Kalender Atak
A1 Ibrahim Ihsan Taskiran
A1 Christopher Flerin
A1 David Mauduit
A1 Liesbeth Minnoye
A1 Gert Hulsemans
A1 Valerie Christiaens
A1 Ghanem-Elias Ghanem
A1 Jasper Wouters
A1 Stein Aerts
YR 2019
UL http://biorxiv.org/content/early/2019/12/23/2019.12.21.885806.abstract
AB 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.