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Visualizing and Annotating Hi-C Data
2021Epigenomics studies require the combined analysis and integration of multiple types of data and annotations to extract biologically relevant information. In this context, sophisticated data visualization techniques are fundamental to identify meaningful patterns in the data in relation to the genomic coordinates.
Pal K, Ferrari F
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Computational Analysis of Hi-C Data
2020The chromatin organization in the 3D nuclear space is essential for genome functionality. This spatial organization encompasses different topologies at diverse scale lengths with chromosomes occupying distinct volumes and individual chromosomes folding into compartments, inside which the chromatin fiber is packed in large domains (as the topologically ...
Forcato M., Bicciato S.
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2021
Processing, storing, and visualizing high-resolution Hi-C data required development of efficient data formats. A sparse matrix format saving only nonzero values has become the norm. A "zoomable" matrix style also became popular, storing multiple resolutions in a single file for interactive visualization.
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Processing, storing, and visualizing high-resolution Hi-C data required development of efficient data formats. A sparse matrix format saving only nonzero values has become the norm. A "zoomable" matrix style also became popular, storing multiple resolutions in a single file for interactive visualization.
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Methods for the Differential Analysis of Hi-C Data
2021The 3D organization of chromatin within the nucleus enables dynamic regulation and cell type-specific transcription of the genome. This is true at multiple levels of resolution: on a large scale, with chromosomes occupying distinct volumes (chromosome territories); at the level of individual chromatin fibers, which are organized into compartmentalized ...
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Methods to Assess the Reproducibility and Similarity of Hi-C Data
2021Hi-C experiments are costly to perform and involve multiple complex experimental steps. Reproducibility of Hi-C data is essential for ensuring the validity of the scientific conclusions drawn from the data. In this chapter, we describe several recently developed computational methods for assessing reproducibility of Hi-C replicate experiments.
Tao, Yang, Xi, He, Lin, An, Qunhua, Li
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Polymer Folding Simulations from Hi-C Data
2021In the absence of a clear molecular understanding of the mechanism that stabilizes specific contacts in interphasic chromatin, we resort to the principle of maximum entropy to build a polymeric model based on the Hi-C data of the specific system one wants to study.
Yinxiu, Zhan +2 more
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Processing and Analysis of Hi-C Data on Bacteria
2018The study of three-dimensional genome organization has recently gained much attention in the context of novel techniques for detecting genome-wide contacts using next-generation sequencing. These genome-wide chromosome conformation capture-based methods, such as Hi-C, give a deep topological insight into the architecture of the genome inside the cell ...
Andreas, Hofmann, Dieter W, Heermann
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3D Genome Reconstruction with ShRec3D+ and Hi-C Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018Hi-C technology, a chromosome conformation capture (3C) based method, has been developed to capture genome-wide interactions at a given resolution. The next challenge is to reconstruct 3D structure of genome from the 3C-derived data computationally.
Jiangeng Li, Wei Zhang, Xiaodan Li
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Analysis of Hi-C Data for Discovery of Structural Variations in Cancer
2021Structural variations (SVs) are large genomic rearrangements that can be challenging to identify with current short read sequencing technology due to various confounding factors such as existence of genomic repeats and complex SV structures. Hi-C breakfinder is the first computational tool that utilizes the technology of high-throughput chromatin ...
Fan, Song +3 more
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