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Nat Commun. 2019 Sep 17;10(1):4221. doi: 10.1038/s41467-019-11950-y.

Identification of significant chromatin contacts from HiChIP data by FitHiChIP.

Author information

1
Division of Vaccine Discovery, La Jolla Institute for Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA.
2
Respiratory Biomedical Research Unit, University of Southampton, University Road, Southampton, SO17 1BJ, UK.
3
School of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
4
Division of Vaccine Discovery, La Jolla Institute for Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA. ferhatay@lji.org.
5
School of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. ferhatay@lji.org.

Abstract

HiChIP/PLAC-seq is increasingly becoming popular for profiling 3D chromatin contacts among regulatory elements and for annotating functions of genetic variants. Here we describe FitHiChIP, a computational method for loop calling from HiChIP/PLAC-seq data, which jointly models the non-uniform coverage and genomic distance scaling of contact counts to compute statistical significance estimates. We also develop a technique to filter putative bystander loops that can be explained by stronger adjacent loops. Compared to existing methods, FitHiChIP performs better in recovering contacts reported by Hi-C, promoter capture Hi-C and ChIA-PET experiments and in capturing previously validated promoter-enhancer interactions. FitHiChIP loop calls are reproducible among replicates and are consistent across different experimental settings. Our work also provides a framework for differential HiChIP analysis with an option to utilize ChIP-seq data for further characterizing differential loops. Even though designed for HiChIP, FitHiChIP is also applicable to other conformation capture assays.

PMID:
31530818
PMCID:
PMC6748947
DOI:
10.1038/s41467-019-11950-y
[Indexed for MEDLINE]
Free PMC Article

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