scHiCcompare: an R package for differential analysis of single-cell Hi-C data

Abstract excerpt

Changes in the three-dimensional (3D) structure of the human genome are key indicators of cancer and developmental disorders. Techniques like chromatin conformation capture (Hi-C) have been developed to study these global 3D structures, typically requiring millions of cells and an extremely high sequencing depth (around 1 billion reads per sample) for bulk Hi-C. In contrast, single-cell Hi-C (scHi-C) captures 3D s...

Topics

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• Algorithms
• Chromatin
• Chromosomes
• Genomics
• Internet
• Polymorphism, Single Nucleotide
• Software

Identifiers and source

Literature Corpus work

315d3af4-0cb3-57a4-9137-26eb7f45d69c

DOI

10.1101/2024.11.06.622369