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Cao, Fan; Zhang, Yu; Cai, Yichao; Animesh, Sambhavi; Zhang, Ying; Akincilar, Semih Can; Loh, Yan Ping; Li, Xinya; Chng, Wee Joo; Tergaonkar, Vinay; Kwoh, Chee Keong; Fullwood, Melissa J
Genome Biology, 08/2021, Letnik: 22, Številka: 1Journal Article
Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. We develop a computational method, chromatin interaction neural network (ChINN), to predict chromatin interactions between open chromatin regions using only DNA sequences. ChINN predicts CTCF- and RNA polymerase II-associated and Hi-C chromatin interactions. ChINN shows good across-sample performances and captures various sequence features for chromatin interaction prediction. We apply ChINN to 6 chronic lymphocytic leukemia (CLL) patient samples and a published cohort of 84 CLL open chromatin samples. Our results demonstrate extensive heterogeneity in chromatin interactions among CLL patient samples.
