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Genes (Basel). 2019 Jul 18;10(7). pii: E548. doi: 10.3390/genes10070548.

Computational Processing and Quality Control of Hi-C, Capture Hi-C and Capture-C Data.

Author information

1
The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA.
2
Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
3
Genomics Unit, Centre for Genomic Regulation, Carrer del Dr. Aiguader 88, 08003 Barcelona, Spain.
4
TRON-Translational Oncology at the University Medical Center of Johannes Gutenberg University, Freiligrathstrasse 12, 55131 Mainz, Germany.
5
Department of Mathematics and Computer Science, Institute of Bioinformatics, FU Berlin, 14195 Berlin, Germany. peter.robinson@jax.org.
6
The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, CT 06032, USA. peter.robinson@jax.org.
7
Institute for Systems Genomics, University of Connecticut, Farmington, CT 06032, USA. peter.robinson@jax.org.

Abstract

Hi-C, capture Hi-C (CHC) and Capture-C have contributed greatly to our present understanding of the three-dimensional organization of genomes in the context of transcriptional regulation by characterizing the roles of topological associated domains, enhancer promoter loops and other three-dimensional genomic interactions. The analysis is based on counts of chimeric read pairs that map to interacting regions of the genome. However, the processing and quality control presents a number of unique challenges. We review here the experimental and computational foundations and explain how the characteristics of restriction digests, sonication fragments and read pairs can be exploited to distinguish technical artefacts from valid read pairs originating from true chromatin interactions.

KEYWORDS:

Hi-C; capture Hi-C; processing; quality control

PMID:
31323892
PMCID:
PMC6678864
DOI:
10.3390/genes10070548
[Indexed for MEDLINE]
Free PMC Article

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