The study presents a method called LACHESIS that uses Hi-C data to improve the accuracy of de novo genome assemblies. Hi-C data provides long-range information about chromatin interactions, which can be used to assign, order, and orient genomic sequences to chromosomes. The method was tested on human, mouse, and fruit fly genomes, achieving high accuracy in assigning scaffolds to chromosome groups and ordering and orienting scaffolds within those groups. The results show that Hi-C data can also be used to validate chromosomal translocations in cancer genomes. The study highlights the importance of using Hi-C data to achieve chromosome-scale contiguity in de novo genome assemblies, which is currently not routinely achieved. The method is scalable and can be applied to a wide range of organisms, making it a valuable tool for genome assembly. The study also discusses the limitations of current de novo assembly methods and the need for scalable, cost-effective approaches to achieve the standards set by the Human Genome Project. The results demonstrate that Hi-C data can significantly improve the accuracy of genome assemblies, particularly for complex regions such as centromeres. The study also shows that Hi-C data can be used to detect chromosomal rearrangements in cancer genomes, which is important for understanding the genetic basis of cancer. Overall, the study provides a new approach for improving the accuracy and contiguity of de novo genome assemblies using Hi-C data.The study presents a method called LACHESIS that uses Hi-C data to improve the accuracy of de novo genome assemblies. Hi-C data provides long-range information about chromatin interactions, which can be used to assign, order, and orient genomic sequences to chromosomes. The method was tested on human, mouse, and fruit fly genomes, achieving high accuracy in assigning scaffolds to chromosome groups and ordering and orienting scaffolds within those groups. The results show that Hi-C data can also be used to validate chromosomal translocations in cancer genomes. The study highlights the importance of using Hi-C data to achieve chromosome-scale contiguity in de novo genome assemblies, which is currently not routinely achieved. The method is scalable and can be applied to a wide range of organisms, making it a valuable tool for genome assembly. The study also discusses the limitations of current de novo assembly methods and the need for scalable, cost-effective approaches to achieve the standards set by the Human Genome Project. The results demonstrate that Hi-C data can significantly improve the accuracy of genome assemblies, particularly for complex regions such as centromeres. The study also shows that Hi-C data can be used to detect chromosomal rearrangements in cancer genomes, which is important for understanding the genetic basis of cancer. Overall, the study provides a new approach for improving the accuracy and contiguity of de novo genome assemblies using Hi-C data.