The 3D organization of the genome plays a key role in many cellular processes, such as gene regulation, differentiation, and replication. Assays like Hi-C measure DNA-DNA contacts in a genome high-throughput fashion. Inferring accurate 3D models of how chromosomes fold from such data can yield insights that are hidden in the raw data. While many methods exist to infer the 3D structure of haploid genomes, inferring a diploid structure from Hi-C data is still an open problem. Indeed, the diploid case is very challenging, as HiC data does not distinguish between homologous chromosomes. We propose here a novel method to infer 3D diploid genomes from Hi-C data.

1. Alexandra Gesine Cauer (gesine@uw.edu)
2. Nelle Varoquaux (nelle.varoquaux@gmail.com)
3. Galip Gürkan Yardımcı (gurkan@uw.edu)
4. Jean-Philippe Vert (Jean-Philippe.Vert@mines-paristech.fr)
5. William Stafford Noble (wnoble@uw.edu)

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