학술논문
Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences
Document Type
article
Author
Source
Genome Biology, Vol 22, Iss 1, Pp 1-25 (2021)
Subject
Language
English
ISSN
1474-760X
Abstract
Abstract 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.