Learning representations of chromatin contacts using a recurrent neural network identifies genomic drivers of conformation

Abstract

Despite the availability of chromatin conformation capture experiments, discerning the relationship between the 1D genome and 3D conformation remains a challenge. Here, the authors propose a method that produces low-dimensional latent representations that summarize intra-chromosomal Hi-C contacts.